Director, Machine Learning Science - Content AI Our Technology Team partners with teams across Expedia Group to create innovative products, services, and tools that deliver high-quality experiences for travelers, partners, and our employees. A single technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction. Introduction to the Team We're seeking a Director of Machine Learning Science to lead our Content AI strategy and execution. In this pivotal role, you will move beyond traditional ML applications to architect the next generation of our Content Engine. You will leverage Large Language Models (LLMs), Multimodal Modality, Agentic Workflow to ensure that every image, review, property description, and video is not only relevant but inspiring, safe, and hyper-personalized. Responsibilities Define the Content AI Strategy: Establish the technical roadmap and OKRs for the Machine Learning systems that power Content Generation, Content Moderation, and Content Relevance across our global ecosystem. Lead AI Innovation: Spearhead the deployment of cutting edge AI solutions (LLMs, Diffusion Models) to automate content creation (text, image, video) and summarization, enhancing discovery on both app and web platforms. Pioneer Agentic Workflows: Drive the research and development of autonomous AI Agents capable of reasoning over vast content repositories to answer complex traveler queries and perform multi-step planning tasks. Master Content Relevance & Safety: Oversee the development of models that rank and personalize content to improve conversion and loyalty, while simultaneously building robust automated moderation pipelines to ensure brand safety, trust, and quality at scale. Bridge the Gap between Research & Product: Prioritize efforts between foundational platform migration/optimization and cutting edge experimentation with new GenAI features. Influence & Collaborate: Foster cross functional partnerships with Product, Engineering, Legal, and Supply teams to integrate AI generated content into the core user experience seamlessly. Build a World Class Team: Recruit, mentor, and manage a high performing team of Applied Scientists and AI Engineers, fostering a culture of technical excellence and rapid experimentation. Minimum Qualifications Graduate degree (PhD preferred) in Computer Science, Artificial Intelligence, Computational Linguistics, or equivalent experience. 12+ years of experience in Machine Learning Science with a specific focus on NLP, Computer Vision, or Recommender Systems. 5+ years of people management experience, with a track record of leading high performing science teams in a tech first environment. Hands on experience with Generative AI technologies (e.g., Transformer architectures, LLMs like LLaMA/GPT, RAG pipelines, PEFT/LoRA fine tuning). Understanding of hallucination, latency, and cost optimization. Proven experience in the Content ML/AI space, specifically regarding Content Understanding, Moderation, Generation, and Relevance, creating rich and immersive user experiences. A proven track record of taking high risk, high reward ML projects from proof of concept to large scale production serving millions of users. Preferred Qualifications Agentic AI Experience: Experience building and deploying Agentic workflows with tool use, planning, and reasoning capabilities. Ability to translate complex AI concepts into clear business value for executive stakeholders. Pay Range: Total cash base $242,000.00 to $338,500.00 in San Jose. Potential to increase salary up to $387,000.00 based on performance. Starting pay varies by location, budget, and experience. Benefits: medical/dental/vision, paid time off, Employee Assistance Program, wellness & travel reimbursement, travel discounts, International Airlines Travel Agent membership. View our full list of benefits. Accommodation Requests If you need assistance with any part of the application or recruiting process due to a disability or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request. Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.
May 05, 2026
Full time
Director, Machine Learning Science - Content AI Our Technology Team partners with teams across Expedia Group to create innovative products, services, and tools that deliver high-quality experiences for travelers, partners, and our employees. A single technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction. Introduction to the Team We're seeking a Director of Machine Learning Science to lead our Content AI strategy and execution. In this pivotal role, you will move beyond traditional ML applications to architect the next generation of our Content Engine. You will leverage Large Language Models (LLMs), Multimodal Modality, Agentic Workflow to ensure that every image, review, property description, and video is not only relevant but inspiring, safe, and hyper-personalized. Responsibilities Define the Content AI Strategy: Establish the technical roadmap and OKRs for the Machine Learning systems that power Content Generation, Content Moderation, and Content Relevance across our global ecosystem. Lead AI Innovation: Spearhead the deployment of cutting edge AI solutions (LLMs, Diffusion Models) to automate content creation (text, image, video) and summarization, enhancing discovery on both app and web platforms. Pioneer Agentic Workflows: Drive the research and development of autonomous AI Agents capable of reasoning over vast content repositories to answer complex traveler queries and perform multi-step planning tasks. Master Content Relevance & Safety: Oversee the development of models that rank and personalize content to improve conversion and loyalty, while simultaneously building robust automated moderation pipelines to ensure brand safety, trust, and quality at scale. Bridge the Gap between Research & Product: Prioritize efforts between foundational platform migration/optimization and cutting edge experimentation with new GenAI features. Influence & Collaborate: Foster cross functional partnerships with Product, Engineering, Legal, and Supply teams to integrate AI generated content into the core user experience seamlessly. Build a World Class Team: Recruit, mentor, and manage a high performing team of Applied Scientists and AI Engineers, fostering a culture of technical excellence and rapid experimentation. Minimum Qualifications Graduate degree (PhD preferred) in Computer Science, Artificial Intelligence, Computational Linguistics, or equivalent experience. 12+ years of experience in Machine Learning Science with a specific focus on NLP, Computer Vision, or Recommender Systems. 5+ years of people management experience, with a track record of leading high performing science teams in a tech first environment. Hands on experience with Generative AI technologies (e.g., Transformer architectures, LLMs like LLaMA/GPT, RAG pipelines, PEFT/LoRA fine tuning). Understanding of hallucination, latency, and cost optimization. Proven experience in the Content ML/AI space, specifically regarding Content Understanding, Moderation, Generation, and Relevance, creating rich and immersive user experiences. A proven track record of taking high risk, high reward ML projects from proof of concept to large scale production serving millions of users. Preferred Qualifications Agentic AI Experience: Experience building and deploying Agentic workflows with tool use, planning, and reasoning capabilities. Ability to translate complex AI concepts into clear business value for executive stakeholders. Pay Range: Total cash base $242,000.00 to $338,500.00 in San Jose. Potential to increase salary up to $387,000.00 based on performance. Starting pay varies by location, budget, and experience. Benefits: medical/dental/vision, paid time off, Employee Assistance Program, wellness & travel reimbursement, travel discounts, International Airlines Travel Agent membership. View our full list of benefits. Accommodation Requests If you need assistance with any part of the application or recruiting process due to a disability or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request. Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.
Please note this role is offered as an initial 6 month fixed term contract on a PAYE basis Lyst is a global fashion shopping platform founded in London in 2010 and catering to over 160M shoppers per year. We offer our customers the largest assortment of premium & luxury fashion products in one place, curating pieces from 27,000 of the world's leading brands and stores. In 2025, Lyst joined Zozo, operators of Zozotown, the leading fashion e commerce platform in Japan. This partnership marks a bold new era for Lyst, as we accelerate our vision and work together to transform the future of fashion shopping through AI and technology. At Lyst, we obsess over the customer, providing a search & discovery experience which offers inspiration, fulfilment, and personalisation. We believe that fashion is amazing but shopping for fashion often isn't, and use our technology, data and creativity to bring more joy, greater choice and fewer fails. Our mission is to help fashion shoppers make better choices and help fashion partners find better audiences as the category leading destination for every fashion shopper. The Role We're looking for a technically strong Product Manager to lead our Affiliate Operations product team, and be the primary Lyst owner for our partnership with ZOZO's Data Science team in New Zealand. Lyst became part of the ZOZO group last year, and this role will work closely with ZOZO's R&D teams to turn research into productionised product data improvements. You will be accountable for the quality, reliability and discoverability of the world's largest product catalogue, powering discovery and commerce across Lyst. Crucially, you will also support Lyst's commercial initiatives from a TPM perspective - shaping the product and data work to accelerate product merging and enrichment. You'll be the lead Lyst contact for ZOZO's Data Science department and will run regular meetings, define joint milestones and translate data science research into Lyst production work. Together you'll accelerate product merging and enrichment while ensuring tooling is production ready. This role is highly cross functional and strategic. If you enjoy being technical, shipping data products, and managing a data science partnership to deliver measurable business outcomes, this is for you. What you'll own Affiliate Operations strategy & roadmap - Prioritise initiatives that raise data quality, completeness and coherence, and ensure delivery of outcomes that improve discovery and checkout metrics. Data foundations & pipelines - Working with engineering, to define product data models and taxonomies and own product data quality KPIs and remediation workflows. Ensure enrichment and merging flows are implemented and monitored. Partnership with ZOZO Data Science (NZ) - Be the primary Lyst lead managing the relationship with ZOZO's data science team: align roadmaps, define experiments, translate research into production requirements, agree on data contracts/security/IP terms, and run regular syncs and reviews. ZOZO collaboration is a core part of our product enrichment work. Operational ownership - Set and measure SLAs for data freshness, accuracy and output quality. Ensure handoffs and runbooks for the Affiliate Operations team are clear. Commercial & stakeholder management - Liaise with Partnerships and Commercial teams to align product data priorities to business objectives (e.g. ROAS bidding algorithms). People & process - Lead the Affiliate Operations product practice: improve team rituals, prioritisation and delivery cadence. Day to day responsibilities Create and maintain an outcome driven roadmap for Affiliate Operations and our commercial roadmap. Translate ZOZO data science outputs (enrichments/merges/flags) into production requirements, APIs and acceptance criteria. Run regular cross organisation planning with ZOZO and Affiliate Operations, including quarterly planning and technical workshops; manage time zone differences and ensure clear asynchronous handovers. Define and track OKRs tied to listings quality and commercial outcomes. Build the backlog and intake process for operational work, tooling requests and BAU. Communicate progress and trade offs clearly to senior stakeholders. Qualifications 3-6+ years product management experience, with a technical/data focus (hands on TPM or Senior TPM). Strong technical literacy: comfortable with APIs, data schemas, ETL/ingestion pipelines and product data modelling. Experience working with data scientists and engineering teams to productise models and features for production. Proven stakeholder management and delivery track record - you can run complex cross functional projects and manage external technical partners. Excellent written and verbal communication; experience coordinating across time zones and cultures. Agile delivery experience and a bias toward measurable outcomes. Nice to have Experience in ecommerce marketplaces or affiliate commerce. Exposure to machine learning/MLops or productionising ML models. Prior experience working with an external data science partner or international R&D partner. Familiarity with taxonomy design, entity resolution and image/data enrichment workstreams. Experience working with affiliate operations or merchant operations teams. Our Ways of Working Office Days: We all come into the office on Tuesdays and Thursdays, with the option to work remotely or come into the office on the other days. Time Off: In addition to the 8 statutory bank holidays, you will receive 29 holidays per year. Lyst's holiday year runs from 1 April to 31 March. Remote Working: Work from anywhere for up to 4 weeks per year. Competitive Family Leave Package: This includes Enhanced Family Leave for those eligible, paid Time off for Dependents and Support for Fertility Treatment & Loss. Clothing Benefit: We provide you with a clothing allowance to use on Lyst every year. This starts at £250 when you join and increases up to £1,000 with your length of service. Private Healthcare: Our healthcare provider is Vitality. Your health is important to us which is why we offer all employees a comprehensive healthcare scheme from the day you start. Training Allowance: All employees are entitled to an annual training allowance of £1,000 for conferences, industry events, training courses and to purchase resources. Pension Scheme: Our pension provider is The People's Pension. We offer a minimum employee contribution of 5% and 3% employer contribution. Eye Tests and Vouchers: Employees can make a saving on their eye test and glasses through our chosen provider. You'll receive a free eye test every year and a discount towards glasses. Cycle-to-Work Scheme: Lyst will purchase a bicycle from your chosen retailer, and you will receive a voucher to pick up your bicycle from them. Transport Season Ticket Loan: Employees can apply for an interest free season ticket loan to support your travel to work. Social Events: Frequent company wide social events including Christmas & summer parties, sports days, themed drinks, quizzes, cook alongs, as well as smaller team socials. We also have plenty of interest based groups such as football, running club, book club, culinary and more.
May 05, 2026
Full time
Please note this role is offered as an initial 6 month fixed term contract on a PAYE basis Lyst is a global fashion shopping platform founded in London in 2010 and catering to over 160M shoppers per year. We offer our customers the largest assortment of premium & luxury fashion products in one place, curating pieces from 27,000 of the world's leading brands and stores. In 2025, Lyst joined Zozo, operators of Zozotown, the leading fashion e commerce platform in Japan. This partnership marks a bold new era for Lyst, as we accelerate our vision and work together to transform the future of fashion shopping through AI and technology. At Lyst, we obsess over the customer, providing a search & discovery experience which offers inspiration, fulfilment, and personalisation. We believe that fashion is amazing but shopping for fashion often isn't, and use our technology, data and creativity to bring more joy, greater choice and fewer fails. Our mission is to help fashion shoppers make better choices and help fashion partners find better audiences as the category leading destination for every fashion shopper. The Role We're looking for a technically strong Product Manager to lead our Affiliate Operations product team, and be the primary Lyst owner for our partnership with ZOZO's Data Science team in New Zealand. Lyst became part of the ZOZO group last year, and this role will work closely with ZOZO's R&D teams to turn research into productionised product data improvements. You will be accountable for the quality, reliability and discoverability of the world's largest product catalogue, powering discovery and commerce across Lyst. Crucially, you will also support Lyst's commercial initiatives from a TPM perspective - shaping the product and data work to accelerate product merging and enrichment. You'll be the lead Lyst contact for ZOZO's Data Science department and will run regular meetings, define joint milestones and translate data science research into Lyst production work. Together you'll accelerate product merging and enrichment while ensuring tooling is production ready. This role is highly cross functional and strategic. If you enjoy being technical, shipping data products, and managing a data science partnership to deliver measurable business outcomes, this is for you. What you'll own Affiliate Operations strategy & roadmap - Prioritise initiatives that raise data quality, completeness and coherence, and ensure delivery of outcomes that improve discovery and checkout metrics. Data foundations & pipelines - Working with engineering, to define product data models and taxonomies and own product data quality KPIs and remediation workflows. Ensure enrichment and merging flows are implemented and monitored. Partnership with ZOZO Data Science (NZ) - Be the primary Lyst lead managing the relationship with ZOZO's data science team: align roadmaps, define experiments, translate research into production requirements, agree on data contracts/security/IP terms, and run regular syncs and reviews. ZOZO collaboration is a core part of our product enrichment work. Operational ownership - Set and measure SLAs for data freshness, accuracy and output quality. Ensure handoffs and runbooks for the Affiliate Operations team are clear. Commercial & stakeholder management - Liaise with Partnerships and Commercial teams to align product data priorities to business objectives (e.g. ROAS bidding algorithms). People & process - Lead the Affiliate Operations product practice: improve team rituals, prioritisation and delivery cadence. Day to day responsibilities Create and maintain an outcome driven roadmap for Affiliate Operations and our commercial roadmap. Translate ZOZO data science outputs (enrichments/merges/flags) into production requirements, APIs and acceptance criteria. Run regular cross organisation planning with ZOZO and Affiliate Operations, including quarterly planning and technical workshops; manage time zone differences and ensure clear asynchronous handovers. Define and track OKRs tied to listings quality and commercial outcomes. Build the backlog and intake process for operational work, tooling requests and BAU. Communicate progress and trade offs clearly to senior stakeholders. Qualifications 3-6+ years product management experience, with a technical/data focus (hands on TPM or Senior TPM). Strong technical literacy: comfortable with APIs, data schemas, ETL/ingestion pipelines and product data modelling. Experience working with data scientists and engineering teams to productise models and features for production. Proven stakeholder management and delivery track record - you can run complex cross functional projects and manage external technical partners. Excellent written and verbal communication; experience coordinating across time zones and cultures. Agile delivery experience and a bias toward measurable outcomes. Nice to have Experience in ecommerce marketplaces or affiliate commerce. Exposure to machine learning/MLops or productionising ML models. Prior experience working with an external data science partner or international R&D partner. Familiarity with taxonomy design, entity resolution and image/data enrichment workstreams. Experience working with affiliate operations or merchant operations teams. Our Ways of Working Office Days: We all come into the office on Tuesdays and Thursdays, with the option to work remotely or come into the office on the other days. Time Off: In addition to the 8 statutory bank holidays, you will receive 29 holidays per year. Lyst's holiday year runs from 1 April to 31 March. Remote Working: Work from anywhere for up to 4 weeks per year. Competitive Family Leave Package: This includes Enhanced Family Leave for those eligible, paid Time off for Dependents and Support for Fertility Treatment & Loss. Clothing Benefit: We provide you with a clothing allowance to use on Lyst every year. This starts at £250 when you join and increases up to £1,000 with your length of service. Private Healthcare: Our healthcare provider is Vitality. Your health is important to us which is why we offer all employees a comprehensive healthcare scheme from the day you start. Training Allowance: All employees are entitled to an annual training allowance of £1,000 for conferences, industry events, training courses and to purchase resources. Pension Scheme: Our pension provider is The People's Pension. We offer a minimum employee contribution of 5% and 3% employer contribution. Eye Tests and Vouchers: Employees can make a saving on their eye test and glasses through our chosen provider. You'll receive a free eye test every year and a discount towards glasses. Cycle-to-Work Scheme: Lyst will purchase a bicycle from your chosen retailer, and you will receive a voucher to pick up your bicycle from them. Transport Season Ticket Loan: Employees can apply for an interest free season ticket loan to support your travel to work. Social Events: Frequent company wide social events including Christmas & summer parties, sports days, themed drinks, quizzes, cook alongs, as well as smaller team socials. We also have plenty of interest based groups such as football, running club, book club, culinary and more.
About AQEMIA AQEMIA is a drug invention company dedicated to creating entirely new medicines to address major unmet medical needs. At the core of our mission is QEMI, our proprietary molecule-invention platform, which uniquely combines cutting edge science with advanced technology. Powered by physics based modeling, statistical mechanics, and generative AI, QEMI allows our teams to design novel drug candidates from first principles. About our Team AQEMIA brings together a diverse, multidisciplinary team of 65+ professionals based in Paris and London. Our scientists and engineers-including chemists, physicists, machine learning experts, and software engineers-work side by side to push the boundaries of early stage drug discovery. About the Team The mission of the Molecular Simulations Team is threefold: Support drug discovery programs by maximizing the impact of binding free energy calculations in decision making. Build, benchmark and continuously improve reproducible and scalable pipelines for binding free energy calculations, enabling support for multiple programs in parallel. Collaborate closely with our Physics Research Team to integrate innovations from AQEMIA's proprietary binding free energy methods. Role Overview As a Senior Application Research Scientist in the Molecular Simulations Team, you will be a scientific leader and technical expert, contributing to the strategy and delivery of AQEMIA's Binding Free Energy Technology. You will help define and evolve how physics based simulations inform and accelerate drug discovery decisions at AQEMIA. Key Responsibilities Design and lead large scale simulation studies (e.g., relative and absolute binding free energy predictions). Evaluate and improve modelling protocols for reproducibility, accuracy, and efficiency. Serve as a mentor to junior scientists, promoting best practices in simulation and analysis. Contribute to cross functional planning and the integration of simulations with experimental and AI based insights. Stay at the forefront of developments in molecular simulations and suggest innovations to the team. Support the development and scaling of workflows that can serve multiple drug discovery projects. Work closely with the Research Team to implement improvements and updates to AQEMIA's proprietary binding free energy methods. Qualifications & Experience PhD in Computational Chemistry, Biophysics, Statistical Mechanics, or related discipline. 5+ years of experience in molecular simulations, ideally within an industrial drug discovery context. Deep knowledge of free energy methods, molecular dynamics, and simulation software. Experience running and analysing binding free energy calculations. Strong programming/scripting ability (Python) and experience with code sharing platforms (GitHub). Demonstrated ability to lead scientific projects and communicate effectively across disciplines. Nice to Have Experience in machine learning applications for physics based modelling. Track record of scientific publications and contributions to the computational drug discovery community. Preferred Mindset Scientific Rigour: Champion high scientific standards and promote best practices across the team. Humble and Willing to Learn: Lead by example with curiosity and openness to new ideas. Excited by Challenging Scientific Problems: Passionate about solving complex, cutting edge problems and guiding others through them. Pragmatic and Impact Driven: Combine strategic thinking with practical execution to deliver real world impact in a fast paced environment. Leadership through Influence: Inspire and mentor colleagues while fostering a collaborative, high performance culture. Application Deadline We will be accepting applications until 14th April. Once the role closes, our team will review all submissions and reach out to candidates selected for interview. Benefits Expanding Drug Discovery Pipeline: Focused on critical therapeutic areas such as Oncology, CNS, and Immuno inflammation, with in vivo proof of concept and patent stage programs. Collaborations with top Pharma, including a $140M Sanofi deal. World Class Interdisciplinary Team: Work alongside exceptional talent at the intersection of technology and life sciences. DeepTech Recognition: AQEMIA is proud to be part of the French Tech 120 and France 2030, highlighting our role as a key player in Europe's DeepTech ecosystem. Prime Location with Flexibility: Offices located in the heart of Paris and London (King's Cross), with flexible work arrangements including up to two remote days per week. Strong Financial Backing: $100M raised from leading European and International investors.
May 05, 2026
Full time
About AQEMIA AQEMIA is a drug invention company dedicated to creating entirely new medicines to address major unmet medical needs. At the core of our mission is QEMI, our proprietary molecule-invention platform, which uniquely combines cutting edge science with advanced technology. Powered by physics based modeling, statistical mechanics, and generative AI, QEMI allows our teams to design novel drug candidates from first principles. About our Team AQEMIA brings together a diverse, multidisciplinary team of 65+ professionals based in Paris and London. Our scientists and engineers-including chemists, physicists, machine learning experts, and software engineers-work side by side to push the boundaries of early stage drug discovery. About the Team The mission of the Molecular Simulations Team is threefold: Support drug discovery programs by maximizing the impact of binding free energy calculations in decision making. Build, benchmark and continuously improve reproducible and scalable pipelines for binding free energy calculations, enabling support for multiple programs in parallel. Collaborate closely with our Physics Research Team to integrate innovations from AQEMIA's proprietary binding free energy methods. Role Overview As a Senior Application Research Scientist in the Molecular Simulations Team, you will be a scientific leader and technical expert, contributing to the strategy and delivery of AQEMIA's Binding Free Energy Technology. You will help define and evolve how physics based simulations inform and accelerate drug discovery decisions at AQEMIA. Key Responsibilities Design and lead large scale simulation studies (e.g., relative and absolute binding free energy predictions). Evaluate and improve modelling protocols for reproducibility, accuracy, and efficiency. Serve as a mentor to junior scientists, promoting best practices in simulation and analysis. Contribute to cross functional planning and the integration of simulations with experimental and AI based insights. Stay at the forefront of developments in molecular simulations and suggest innovations to the team. Support the development and scaling of workflows that can serve multiple drug discovery projects. Work closely with the Research Team to implement improvements and updates to AQEMIA's proprietary binding free energy methods. Qualifications & Experience PhD in Computational Chemistry, Biophysics, Statistical Mechanics, or related discipline. 5+ years of experience in molecular simulations, ideally within an industrial drug discovery context. Deep knowledge of free energy methods, molecular dynamics, and simulation software. Experience running and analysing binding free energy calculations. Strong programming/scripting ability (Python) and experience with code sharing platforms (GitHub). Demonstrated ability to lead scientific projects and communicate effectively across disciplines. Nice to Have Experience in machine learning applications for physics based modelling. Track record of scientific publications and contributions to the computational drug discovery community. Preferred Mindset Scientific Rigour: Champion high scientific standards and promote best practices across the team. Humble and Willing to Learn: Lead by example with curiosity and openness to new ideas. Excited by Challenging Scientific Problems: Passionate about solving complex, cutting edge problems and guiding others through them. Pragmatic and Impact Driven: Combine strategic thinking with practical execution to deliver real world impact in a fast paced environment. Leadership through Influence: Inspire and mentor colleagues while fostering a collaborative, high performance culture. Application Deadline We will be accepting applications until 14th April. Once the role closes, our team will review all submissions and reach out to candidates selected for interview. Benefits Expanding Drug Discovery Pipeline: Focused on critical therapeutic areas such as Oncology, CNS, and Immuno inflammation, with in vivo proof of concept and patent stage programs. Collaborations with top Pharma, including a $140M Sanofi deal. World Class Interdisciplinary Team: Work alongside exceptional talent at the intersection of technology and life sciences. DeepTech Recognition: AQEMIA is proud to be part of the French Tech 120 and France 2030, highlighting our role as a key player in Europe's DeepTech ecosystem. Prime Location with Flexibility: Offices located in the heart of Paris and London (King's Cross), with flexible work arrangements including up to two remote days per week. Strong Financial Backing: $100M raised from leading European and International investors.
Cognite operates at the forefront of industrial digitalization, building AI, and data solutions that solve the world's hardest, highest-impact problems. With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements. We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not backwards - you'll feel right at home here. Our Moonshot is bold: Unlock $100B in customer value by 2035, and redefine how global industry works. Join us in this venture where AI and data meet ingenuity, and together, we will forge the path to a smarter, more connected industrial future. How you'll demonstrate Ownership As the Data Science (DS) Leader for Value Delivery Europe, you will own and elevate the Data Science capability across the region. Your primary mission is to build a high-performing team of Data Scientists who deliver scalable, production-ready analytical and agentic solutions that accelerate customer value on Cognite Data Fusion and Dune. You will be responsible for the professional development, methods, quality standards, and delivery excellence of the DS profession while coaching Data Scientists to operate as trusted technical advisors in industrial AI and data-driven workflows. You will ensure DS engagements are repeatable, efficient, customer-centric, and aligned with Cognite's delivery standards. This is a capability-building role-your time spent on billable or customer-facing execution will be limited to 20%, ensuring your focus remains on uplifting the DS community, maturing practices, and driving consistency and technical excellence across pods. The Impact you bring to Cognite Regional Technical Leadership (Data Science) Own the DS function's technical quality across all customer engagements in the region Set and maintain standards for modelling quality, agentic workflows, industrial analytics, data validation, and performance testing Ensure scalable, maintainable, and well-documented analytical solutions across all pods. Champion DS solutions that translate industrial challenges into measurable, value-oriented outcomes Guide teams on interpreting KPI impact, validating model performance, and ensuring business stakeholders understand insights and outputs. Support escalations as a senior technical advisor-ensuring pragmatic, customer centric resolution Scaling & Growth Partner with Sales and Product to ensure DS technical feasibility in scoping and expansions. Ensure DS work accelerates adoption of AI enabled workflows, Dune based solutions, and repeatable industrial patterns. Drive standardization of DS approaches, templates, benchmark metrics, and reusable assets to scale the function. Operational & Delivery Quality Management Ensure DS teams follow disciplined delivery practices including: - clear problem framing - structured exploration - robust modelling & validation - well defined acceptance criteria - telemetry, monitoring, and performance checks Improve portfolio predictability by aligning DS work with PM governance, architecture guidelines, and data engineering readiness. Track DS contribution to delivery health, model quality, and customer outcomes. Lead, mentor, and develop the Data Science community across Value Delivery Europe. Define the DS competency framework and build learning pathways covering: - statistics, machine learning, optimisation - deep learning, generative models, agentic frameworks - industrial domain context - Dune workflows and UI based logic - communication, consulting, and delivery excellence Run DS guilds, brown bags, technical shows and tells, and practice reviews. Recruit top DS talent, shape onboarding, and grow internal leaders. Ensure DS teams work seamlessly with PMs, Solution Architects, Data Engineers, Product Ambassadors, and Customer Success. Provide structured feedback loops to Product and Engineering on tooling gaps, bugs, and feature improvements. Support cross functional alignment on best practices for modelling, data readiness, and solution reliability Required Qualifications 7-10+ years in Data Science, Machine Learning, Agentic systems, or industrial analytics roles Proven track record delivering data driven solutions in production-preferably in industrial, asset heavy, or mission critical environments Experience leading technical teams or DS communities Strong applied background in mathematics, statistics, ML, optimisation, or agentic workflows. Ability to translate industrial problems into analytical, predictive, or agent based solutions Familiarity with full stack DS: - backend logic (Python/SQL/pipelines) - UI/workflow experience (Dune, low code/no code, visual interfaces) Excellent communication skills-able to explain complex technical concepts to non technical stakeholders High delivery orientation with strong problem solving and analytical thinking Mindset: Passionate about growing people, uplifting technical depth, and maturing DS practices Curious, experimental, and willing to adopt new frameworks, including Dune based development Collaborative, structured, and committed to customer value and operational excellence Thrives in high growth, rapidly evolving environments A snapshot of our many perks and benefits as a Cogniter Join an organization of 60 different nationalities with Diversity, Equality and Inclusion (DEI) in focus A highly modern and fun working environment with sublime culture across the organization, follow us on to know more Flat structure with direct access to decision makers Opportunity to work with and learn from some of the best people on some of the most ambitious projects found anywhere, across industries, with cutting edge technology Join ourHUB ️ to be part of the conversation directly with Cogniters and our partners. Get access to private health services with Cognite Care. Hungry? We've got your back. A subsidized lunch at the canteen is delivered by the chefs at Fornebuporten (Aker Tech House) Our ownCognite exclusive coffee bar with the friendliest baristas is here to brew coffee for coffee lovers, tea for tea lovers, smoothie for smoothie lovers, and the baristas creative concoctions when the mood strikes. We take your mental and physical health seriously by having a broad health offering and a free membership to our fully staffed gym on site. We're globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi. Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment.
May 05, 2026
Full time
Cognite operates at the forefront of industrial digitalization, building AI, and data solutions that solve the world's hardest, highest-impact problems. With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements. We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not backwards - you'll feel right at home here. Our Moonshot is bold: Unlock $100B in customer value by 2035, and redefine how global industry works. Join us in this venture where AI and data meet ingenuity, and together, we will forge the path to a smarter, more connected industrial future. How you'll demonstrate Ownership As the Data Science (DS) Leader for Value Delivery Europe, you will own and elevate the Data Science capability across the region. Your primary mission is to build a high-performing team of Data Scientists who deliver scalable, production-ready analytical and agentic solutions that accelerate customer value on Cognite Data Fusion and Dune. You will be responsible for the professional development, methods, quality standards, and delivery excellence of the DS profession while coaching Data Scientists to operate as trusted technical advisors in industrial AI and data-driven workflows. You will ensure DS engagements are repeatable, efficient, customer-centric, and aligned with Cognite's delivery standards. This is a capability-building role-your time spent on billable or customer-facing execution will be limited to 20%, ensuring your focus remains on uplifting the DS community, maturing practices, and driving consistency and technical excellence across pods. The Impact you bring to Cognite Regional Technical Leadership (Data Science) Own the DS function's technical quality across all customer engagements in the region Set and maintain standards for modelling quality, agentic workflows, industrial analytics, data validation, and performance testing Ensure scalable, maintainable, and well-documented analytical solutions across all pods. Champion DS solutions that translate industrial challenges into measurable, value-oriented outcomes Guide teams on interpreting KPI impact, validating model performance, and ensuring business stakeholders understand insights and outputs. Support escalations as a senior technical advisor-ensuring pragmatic, customer centric resolution Scaling & Growth Partner with Sales and Product to ensure DS technical feasibility in scoping and expansions. Ensure DS work accelerates adoption of AI enabled workflows, Dune based solutions, and repeatable industrial patterns. Drive standardization of DS approaches, templates, benchmark metrics, and reusable assets to scale the function. Operational & Delivery Quality Management Ensure DS teams follow disciplined delivery practices including: - clear problem framing - structured exploration - robust modelling & validation - well defined acceptance criteria - telemetry, monitoring, and performance checks Improve portfolio predictability by aligning DS work with PM governance, architecture guidelines, and data engineering readiness. Track DS contribution to delivery health, model quality, and customer outcomes. Lead, mentor, and develop the Data Science community across Value Delivery Europe. Define the DS competency framework and build learning pathways covering: - statistics, machine learning, optimisation - deep learning, generative models, agentic frameworks - industrial domain context - Dune workflows and UI based logic - communication, consulting, and delivery excellence Run DS guilds, brown bags, technical shows and tells, and practice reviews. Recruit top DS talent, shape onboarding, and grow internal leaders. Ensure DS teams work seamlessly with PMs, Solution Architects, Data Engineers, Product Ambassadors, and Customer Success. Provide structured feedback loops to Product and Engineering on tooling gaps, bugs, and feature improvements. Support cross functional alignment on best practices for modelling, data readiness, and solution reliability Required Qualifications 7-10+ years in Data Science, Machine Learning, Agentic systems, or industrial analytics roles Proven track record delivering data driven solutions in production-preferably in industrial, asset heavy, or mission critical environments Experience leading technical teams or DS communities Strong applied background in mathematics, statistics, ML, optimisation, or agentic workflows. Ability to translate industrial problems into analytical, predictive, or agent based solutions Familiarity with full stack DS: - backend logic (Python/SQL/pipelines) - UI/workflow experience (Dune, low code/no code, visual interfaces) Excellent communication skills-able to explain complex technical concepts to non technical stakeholders High delivery orientation with strong problem solving and analytical thinking Mindset: Passionate about growing people, uplifting technical depth, and maturing DS practices Curious, experimental, and willing to adopt new frameworks, including Dune based development Collaborative, structured, and committed to customer value and operational excellence Thrives in high growth, rapidly evolving environments A snapshot of our many perks and benefits as a Cogniter Join an organization of 60 different nationalities with Diversity, Equality and Inclusion (DEI) in focus A highly modern and fun working environment with sublime culture across the organization, follow us on to know more Flat structure with direct access to decision makers Opportunity to work with and learn from some of the best people on some of the most ambitious projects found anywhere, across industries, with cutting edge technology Join ourHUB ️ to be part of the conversation directly with Cogniters and our partners. Get access to private health services with Cognite Care. Hungry? We've got your back. A subsidized lunch at the canteen is delivered by the chefs at Fornebuporten (Aker Tech House) Our ownCognite exclusive coffee bar with the friendliest baristas is here to brew coffee for coffee lovers, tea for tea lovers, smoothie for smoothie lovers, and the baristas creative concoctions when the mood strikes. We take your mental and physical health seriously by having a broad health offering and a free membership to our fully staffed gym on site. We're globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi. Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment.
The role We are looking for a motivated and skilled Trait Design Scientist, ideally with a background in photosynthesis research, to drive our R&D initiatives. At Wild, we are building proprietary and "new-to-science" datasets that we use to discover new yield traits. You will play a key role in analysing these datasets and driving the future direction of data collection to accelerate this discovery work. Location We're headquartered in Milton Park, a business and technology park in Oxfordshire. This is an on-site role, though we offer flexibility and hybrid working when possible. Job requirements A PhD in a relevant discipline, e.g. Plant Science, Photosynthesis, Plant Physiology, Bioinformatics. Proven experience delivering complex scientific research projects and driving their strategic direction. Deep theoretical and practical understanding of photosynthesis; you are comfortable interpreting complex physiological data to generate biological hypotheses. Experience using gas exchange and chlorophyll fluorescence systems (e.g. LICORs, Walz), and/or other photosynthetic mechanistic studies used to dissect photosynthetic performance. A strong understanding of the genetic mechanisms that govern plant phenotypes and the factors that influence gene expression. Familiarity with Linux, bioinformatic tools, and the application of machine learning to genomic/phenotype data is highly desirable. A growth-oriented mindset focused on continuous improvement - evaluating new tools and sparking innovation within the team. Ability to distil complex data into clear hypothesis and lead collaborative decision-making sessions. Job responsibilities Lead the design and management of experiments to collect bespoke physiology and genetic datasets across diverse species. Establish robust phenotyping methods and train junior team members to ensure high-quality data collection at scale. Utilise machine learning and bioinformatic tools to mine proprietary datasets, identifying causal genetics behind key photosynthesis traits. Critically evaluate machine learning / AI outputs by integrating photosynthesis expertise with literature reviews and data from our proprietary evolutionary and cell-based platform. Lead trait design sessions, collaborating with other photosynthesis experts, construct engineers, and bioinformaticians to inform phase promotion decisions. Iteratively improve data collection protocols based on the latest photosynthesis research.
May 05, 2026
Full time
The role We are looking for a motivated and skilled Trait Design Scientist, ideally with a background in photosynthesis research, to drive our R&D initiatives. At Wild, we are building proprietary and "new-to-science" datasets that we use to discover new yield traits. You will play a key role in analysing these datasets and driving the future direction of data collection to accelerate this discovery work. Location We're headquartered in Milton Park, a business and technology park in Oxfordshire. This is an on-site role, though we offer flexibility and hybrid working when possible. Job requirements A PhD in a relevant discipline, e.g. Plant Science, Photosynthesis, Plant Physiology, Bioinformatics. Proven experience delivering complex scientific research projects and driving their strategic direction. Deep theoretical and practical understanding of photosynthesis; you are comfortable interpreting complex physiological data to generate biological hypotheses. Experience using gas exchange and chlorophyll fluorescence systems (e.g. LICORs, Walz), and/or other photosynthetic mechanistic studies used to dissect photosynthetic performance. A strong understanding of the genetic mechanisms that govern plant phenotypes and the factors that influence gene expression. Familiarity with Linux, bioinformatic tools, and the application of machine learning to genomic/phenotype data is highly desirable. A growth-oriented mindset focused on continuous improvement - evaluating new tools and sparking innovation within the team. Ability to distil complex data into clear hypothesis and lead collaborative decision-making sessions. Job responsibilities Lead the design and management of experiments to collect bespoke physiology and genetic datasets across diverse species. Establish robust phenotyping methods and train junior team members to ensure high-quality data collection at scale. Utilise machine learning and bioinformatic tools to mine proprietary datasets, identifying causal genetics behind key photosynthesis traits. Critically evaluate machine learning / AI outputs by integrating photosynthesis expertise with literature reviews and data from our proprietary evolutionary and cell-based platform. Lead trait design sessions, collaborating with other photosynthesis experts, construct engineers, and bioinformaticians to inform phase promotion decisions. Iteratively improve data collection protocols based on the latest photosynthesis research.
A leading fashion retailer in Reading is seeking a Data Science & Measurement Lead to manage a team of data scientists focusing on advanced analytics and machine learning. This hybrid role requires expertise in Databricks, Apache Spark, and SQL. You'll be responsible for delivering impactful data solutions, mentoring the team, and collaborating with engineering to ensure data quality. Attractive benefits include healthcare, a generous leave policy, and a bonus potential.
May 05, 2026
Full time
A leading fashion retailer in Reading is seeking a Data Science & Measurement Lead to manage a team of data scientists focusing on advanced analytics and machine learning. This hybrid role requires expertise in Databricks, Apache Spark, and SQL. You'll be responsible for delivering impactful data solutions, mentoring the team, and collaborating with engineering to ensure data quality. Attractive benefits include healthcare, a generous leave policy, and a bonus potential.
Food, Microbiome & Health, Quadram Institute Bioscience Applications are invited for a Postdoctoral Scientist position in the Hildebrand group at the Quadram Institute Bioscience (QIB), Norwich, UK. Background: Microbial fermentation of plant-based foods is increasingly used to recreate the taste, texture, and nutritional qualities of meat, while improving environmental sustainability. Optimizing the production of plant-based foods and ensuring consumer acceptance remain important challenges, further complicated by new and diverse fermentation approaches. The role: In the FlavourFerm consortium, partners are developing novel fermented plant-based foods. This research position will investigate how these foods influence the human gut microbiome and offer potential benefits to host health. Taste and texture of these foods will be predicted from microbial fermentation consortia. Specifically, microbes will be identified that affect fermentation outcomes. Building on previous work from the host group, we will develop machine learning tools to model microbial communities and their impact. In the longer term, this research will support the development of human-centric fermented foods that are safe, appealing, and environmentally sustainable. The environment: The successful applicant will work within the Hildebrand and Traka groups, integrated in the H2020 international FlavourFerm consortium. Prof Hildebrand studies the diversity, interactions, and evolution of microbial communities using high resolution metagenomics and custom software tools. The group is jointly based at QIB and the Earlham Institute developing widely used bioinformatic tools. Dr Traka leads the UK national resource Food & Nutrition National Bioscience Research Infrastructure, focused on automated food categorization using AI. FlavourFerm combines microbiologists, machine learning and food scientists, to develop the next generation of healthy and sustainable nutrition. The project requires close collaborations across Europe; attendance and participation in workshops and consortium meetings is required. The ideal candidate: holds a PhD (or equivalent) in biology, bioinformatics, computer science or a related discipline, being experienced in bioinformatics, (meta)genomic data, and microbiology. Knowledge in AI, machine learning, microbial pathogens, microbiology of fermentation, comparative genomics and analysing microbial communities will be of benefit. Specialized skills will be taught and developed through mentorship and collaborations. Salary on appointment will be within the range £37,500 to £43,350 per annum depending on qualifications and experience. This is a full time post until 30 April 2028. Closing date for applications will be 17 May 2026. Interviews are planned for week commencing 1st June 2026. We are committed to equal opportunities and welcome applications from all sectors of society. The Institute supports equality of opportunity within the workplace and expects all employees to share and display these values. The Institute is an Equality Confident employer.
May 04, 2026
Full time
Food, Microbiome & Health, Quadram Institute Bioscience Applications are invited for a Postdoctoral Scientist position in the Hildebrand group at the Quadram Institute Bioscience (QIB), Norwich, UK. Background: Microbial fermentation of plant-based foods is increasingly used to recreate the taste, texture, and nutritional qualities of meat, while improving environmental sustainability. Optimizing the production of plant-based foods and ensuring consumer acceptance remain important challenges, further complicated by new and diverse fermentation approaches. The role: In the FlavourFerm consortium, partners are developing novel fermented plant-based foods. This research position will investigate how these foods influence the human gut microbiome and offer potential benefits to host health. Taste and texture of these foods will be predicted from microbial fermentation consortia. Specifically, microbes will be identified that affect fermentation outcomes. Building on previous work from the host group, we will develop machine learning tools to model microbial communities and their impact. In the longer term, this research will support the development of human-centric fermented foods that are safe, appealing, and environmentally sustainable. The environment: The successful applicant will work within the Hildebrand and Traka groups, integrated in the H2020 international FlavourFerm consortium. Prof Hildebrand studies the diversity, interactions, and evolution of microbial communities using high resolution metagenomics and custom software tools. The group is jointly based at QIB and the Earlham Institute developing widely used bioinformatic tools. Dr Traka leads the UK national resource Food & Nutrition National Bioscience Research Infrastructure, focused on automated food categorization using AI. FlavourFerm combines microbiologists, machine learning and food scientists, to develop the next generation of healthy and sustainable nutrition. The project requires close collaborations across Europe; attendance and participation in workshops and consortium meetings is required. The ideal candidate: holds a PhD (or equivalent) in biology, bioinformatics, computer science or a related discipline, being experienced in bioinformatics, (meta)genomic data, and microbiology. Knowledge in AI, machine learning, microbial pathogens, microbiology of fermentation, comparative genomics and analysing microbial communities will be of benefit. Specialized skills will be taught and developed through mentorship and collaborations. Salary on appointment will be within the range £37,500 to £43,350 per annum depending on qualifications and experience. This is a full time post until 30 April 2028. Closing date for applications will be 17 May 2026. Interviews are planned for week commencing 1st June 2026. We are committed to equal opportunities and welcome applications from all sectors of society. The Institute supports equality of opportunity within the workplace and expects all employees to share and display these values. The Institute is an Equality Confident employer.
Food, Microbiome & Health, Quadram Institute Bioscience Applications are invited for a Research Scientist (Metaproteomics) to join the Laboratory of Dr Kai Cheng in the Food, Microbiome and Health programme at Quadram Institute Bioscience (QIB), based in Norwich, UK. Since joining the Quadram Institute in 2025 as a Group Leader, Dr Cheng has been leading the AI & Metaproteomics for Human Gut Health group. The group's mission is to advance microbiome research by developing computational methods, large-scale data resources, and AI assisted frameworks for understanding microbial function. The research aims to enable predictive and data driven insights into microbiome systems and their role in human health. We are seeking a highly motivated Research Scientist with a strong interest in metaproteomics and microbiome research. The position focuses on the development and application of computational and analytical methods for metaproteomics, including peptide and protein identification, taxonomic and functional profiling, and integration with other omics data. The successful candidate will work within a multidisciplinary team, applying computational approaches to large scale microbiome datasets and contributing to research aimed at understanding microbial community function in health and disease. This is primarily a computational (dry lab) role, focused on analysing and interpreting metaproteomics data and developing analytical workflows. It involves close collaboration with experimental researchers and requires a solid understanding of proteomics workflows, but does not involve routine laboratory work. The role will also involve the use and development of AI assisted approaches for scientific research, including data driven modelling and the integration of modern AI tools into computational workflows. You will have access to state of the art infrastructure and collaborate with leading researchers in microbiome science and proteomics. This is an excellent opportunity to contribute to cutting edge research while developing expertise in a rapidly growing field. The ideal candidate PhD in Proteomics, Bioinformatics, Computational Biology, or a related discipline. Strong interest in proteomics/metaproteomics and microbiome research. Experience in analysing proteomics or metaproteomics data. Ability to interpret computational results in a meaningful biological context. Proficiency in programming/scripting (e.g. Python, Linux). Strong domain knowledge and scientific understanding in metaproteomics. Motivation and readiness to develop expertise in metaproteomics if direct experience is lacking. Experience in multi omics integration, machine learning, or microbiome data analysis is advantageous. Additional information Salary on appointment will be within the range £37,500 to £45,350 per annum depending on qualifications and experience. This is a full time post for a contract of 24 months. The closing date for applications will be 6 May 2026. Equality, Diversity & Inclusion We are committed to equity, diversity and inclusion, and welcome applications from all sectors of society. The Institute values of Respect, Innovation, Collaboration and Excellence are at the heart of all we do, and we expect all employees to share and display these values. We have a range of family, faith and diversity friendly working arrangements to help all staff achieve excellence in their area of work. As a Disability Confident employer, we guarantee to offer an interview to all disabled applicants who meet the essential criteria for this vacancy. The Quadram Institute Bioscience is a registered charity (No. ) and is an Equal Opportunities Employer.
May 04, 2026
Full time
Food, Microbiome & Health, Quadram Institute Bioscience Applications are invited for a Research Scientist (Metaproteomics) to join the Laboratory of Dr Kai Cheng in the Food, Microbiome and Health programme at Quadram Institute Bioscience (QIB), based in Norwich, UK. Since joining the Quadram Institute in 2025 as a Group Leader, Dr Cheng has been leading the AI & Metaproteomics for Human Gut Health group. The group's mission is to advance microbiome research by developing computational methods, large-scale data resources, and AI assisted frameworks for understanding microbial function. The research aims to enable predictive and data driven insights into microbiome systems and their role in human health. We are seeking a highly motivated Research Scientist with a strong interest in metaproteomics and microbiome research. The position focuses on the development and application of computational and analytical methods for metaproteomics, including peptide and protein identification, taxonomic and functional profiling, and integration with other omics data. The successful candidate will work within a multidisciplinary team, applying computational approaches to large scale microbiome datasets and contributing to research aimed at understanding microbial community function in health and disease. This is primarily a computational (dry lab) role, focused on analysing and interpreting metaproteomics data and developing analytical workflows. It involves close collaboration with experimental researchers and requires a solid understanding of proteomics workflows, but does not involve routine laboratory work. The role will also involve the use and development of AI assisted approaches for scientific research, including data driven modelling and the integration of modern AI tools into computational workflows. You will have access to state of the art infrastructure and collaborate with leading researchers in microbiome science and proteomics. This is an excellent opportunity to contribute to cutting edge research while developing expertise in a rapidly growing field. The ideal candidate PhD in Proteomics, Bioinformatics, Computational Biology, or a related discipline. Strong interest in proteomics/metaproteomics and microbiome research. Experience in analysing proteomics or metaproteomics data. Ability to interpret computational results in a meaningful biological context. Proficiency in programming/scripting (e.g. Python, Linux). Strong domain knowledge and scientific understanding in metaproteomics. Motivation and readiness to develop expertise in metaproteomics if direct experience is lacking. Experience in multi omics integration, machine learning, or microbiome data analysis is advantageous. Additional information Salary on appointment will be within the range £37,500 to £45,350 per annum depending on qualifications and experience. This is a full time post for a contract of 24 months. The closing date for applications will be 6 May 2026. Equality, Diversity & Inclusion We are committed to equity, diversity and inclusion, and welcome applications from all sectors of society. The Institute values of Respect, Innovation, Collaboration and Excellence are at the heart of all we do, and we expect all employees to share and display these values. We have a range of family, faith and diversity friendly working arrangements to help all staff achieve excellence in their area of work. As a Disability Confident employer, we guarantee to offer an interview to all disabled applicants who meet the essential criteria for this vacancy. The Quadram Institute Bioscience is a registered charity (No. ) and is an Equal Opportunities Employer.
Data Science & Measurement Lead Because your new ideas are our way new ways of working. Evolve, your way. We are seeking a Data Science & Measurement Lead to manage and grow a team of data scientists responsible for building advanced analytics, predictive models, and measurement solutions across Primark. This is a hands on role requiring strong technical depth in Databricks, Apache Spark, and SQL. What You'll Get People are at the heart of what we do here, so it's essential we provide you with the right environment to perform at your very best. Let's talk lifestyle: Healthcare, pension, and potential bonus. 27 days of leave, plus bank holidays and if you want, you can buy 5 more. Because Primark is all about tailoring to you, we offer Tax Saver Tickets, fitness centre, and a subsidised cafeteria. This role is a hybrid opportunity, offering 1-2 days Working from home. What You'll Do as a Data Science & Measurement Lead We want you to feel challenged and inspired. Here, you'll develop your skills across a range of responsibilities: Lead a data science team to deliver machine learning models, experimentation frameworks, and measurement solutions that drive measurable business impact. Design, build, and deploy end to end ML pipelines and workflows using Databricks, Spark, Python, SQL, and PySpark. Ensure robust operationalisation of models through scalable, reliable data pipelines and production ready ML systems. Partner closely with engineering teams to optimise distributed compute workloads and uphold data quality, monitoring, and governance standards. Establish and drive best practices in model reproducibility, experiment tracking, and end to end ML lifecycle management. Act as a trusted advisor by sharing deep technical expertise, developing team capability, and managing complex delivery plans. Leverage strong retail domain experience-ideally within apparel or grocery-to translate business needs into effective data driven solutions. What You'll Bring Here at Primark, we want everyone to feel valued - so please bring your authentic self to work, of course with some other key experience and abilities for this role in particular: Extensive hands on experience with Databricks, Apache Spark, advanced SQL, and cloud based lakehouse architectures (Azure, AWS, or GCP), with a strong foundation in statistical modelling and machine learning techniques. Proven ability to deliver measurable commercial value through retail focused data science use cases such as demand forecasting, pricing and promotion effectiveness, allocation, stock optimisation, and waste or shrink reduction. Strong experience in experimental design and causal inference (e.g., A/B testing, quasi experiments), with a clear focus on quantifying incremental value and ensuring insights translate into action. Demonstrated experience taking models from prototype to production, establishing clear success metrics, monitoring, governance, and driving adoption across commercial and operational teams. Ability to shape and prioritise the data science roadmap by balancing business value, data readiness, and delivery risk; applies sound commercial judgement informed by market and industry trends. Proven people leader with experience mentoring and developing high performing data science teams; communicates complex technical concepts clearly to non technical stakeholders and acts as a trusted advisor to the business. Does this sound like you? Great, because we can't wait to see what you'll bring. You'll be supported within a team of equally capable people, celebrating who you are and aiding you reach your potential. At Primark, we're excited about our future - and we're excited to develop yours. About Primark At Primark, people matter. They're the beating heart of our business and the reason we've grown from our first store in Dublin in 1969 to a £9bn+ turnover business and over 80,000 colleagues and over 440 stores in 17 countries today. Our values run through everything we do. In essence, we're Caring and always strive to put people first. We're also Dynamic, bravely pushing the boundaries to stay ahead. And finally, we succeed Together. If you need any reasonable adjustments or have an accessibility request, during your recruitment journey, such as extended time or breaks between online assessments, a sign language interpreter, mobility access, or assistive technology please contact your talent acquisition specialist. All offers of employment are subject to background checks, including right to work, reference education and for some roles criminal, and financial checks. If you have any concerns, please reach out to our talent acquisition team to discuss. Our fashion isn't one size fits all and neither is our culture. Primark promotes equal employment opportunity, we strive to create an inclusive workplace where people can be themselves, access opportunities and thrive together. REQ ID: JR-7582
May 03, 2026
Full time
Data Science & Measurement Lead Because your new ideas are our way new ways of working. Evolve, your way. We are seeking a Data Science & Measurement Lead to manage and grow a team of data scientists responsible for building advanced analytics, predictive models, and measurement solutions across Primark. This is a hands on role requiring strong technical depth in Databricks, Apache Spark, and SQL. What You'll Get People are at the heart of what we do here, so it's essential we provide you with the right environment to perform at your very best. Let's talk lifestyle: Healthcare, pension, and potential bonus. 27 days of leave, plus bank holidays and if you want, you can buy 5 more. Because Primark is all about tailoring to you, we offer Tax Saver Tickets, fitness centre, and a subsidised cafeteria. This role is a hybrid opportunity, offering 1-2 days Working from home. What You'll Do as a Data Science & Measurement Lead We want you to feel challenged and inspired. Here, you'll develop your skills across a range of responsibilities: Lead a data science team to deliver machine learning models, experimentation frameworks, and measurement solutions that drive measurable business impact. Design, build, and deploy end to end ML pipelines and workflows using Databricks, Spark, Python, SQL, and PySpark. Ensure robust operationalisation of models through scalable, reliable data pipelines and production ready ML systems. Partner closely with engineering teams to optimise distributed compute workloads and uphold data quality, monitoring, and governance standards. Establish and drive best practices in model reproducibility, experiment tracking, and end to end ML lifecycle management. Act as a trusted advisor by sharing deep technical expertise, developing team capability, and managing complex delivery plans. Leverage strong retail domain experience-ideally within apparel or grocery-to translate business needs into effective data driven solutions. What You'll Bring Here at Primark, we want everyone to feel valued - so please bring your authentic self to work, of course with some other key experience and abilities for this role in particular: Extensive hands on experience with Databricks, Apache Spark, advanced SQL, and cloud based lakehouse architectures (Azure, AWS, or GCP), with a strong foundation in statistical modelling and machine learning techniques. Proven ability to deliver measurable commercial value through retail focused data science use cases such as demand forecasting, pricing and promotion effectiveness, allocation, stock optimisation, and waste or shrink reduction. Strong experience in experimental design and causal inference (e.g., A/B testing, quasi experiments), with a clear focus on quantifying incremental value and ensuring insights translate into action. Demonstrated experience taking models from prototype to production, establishing clear success metrics, monitoring, governance, and driving adoption across commercial and operational teams. Ability to shape and prioritise the data science roadmap by balancing business value, data readiness, and delivery risk; applies sound commercial judgement informed by market and industry trends. Proven people leader with experience mentoring and developing high performing data science teams; communicates complex technical concepts clearly to non technical stakeholders and acts as a trusted advisor to the business. Does this sound like you? Great, because we can't wait to see what you'll bring. You'll be supported within a team of equally capable people, celebrating who you are and aiding you reach your potential. At Primark, we're excited about our future - and we're excited to develop yours. About Primark At Primark, people matter. They're the beating heart of our business and the reason we've grown from our first store in Dublin in 1969 to a £9bn+ turnover business and over 80,000 colleagues and over 440 stores in 17 countries today. Our values run through everything we do. In essence, we're Caring and always strive to put people first. We're also Dynamic, bravely pushing the boundaries to stay ahead. And finally, we succeed Together. If you need any reasonable adjustments or have an accessibility request, during your recruitment journey, such as extended time or breaks between online assessments, a sign language interpreter, mobility access, or assistive technology please contact your talent acquisition specialist. All offers of employment are subject to background checks, including right to work, reference education and for some roles criminal, and financial checks. If you have any concerns, please reach out to our talent acquisition team to discuss. Our fashion isn't one size fits all and neither is our culture. Primark promotes equal employment opportunity, we strive to create an inclusive workplace where people can be themselves, access opportunities and thrive together. REQ ID: JR-7582
A leading bioscience research institute in the UK is seeking a Postdoctoral Scientist to join the FlavourFerm consortium. The successful candidate will research the influence of fermented plant-based foods on the gut microbiome and develop machine learning tools for modeling microbial communities. A PhD in a relevant field and experience in bioinformatics and microbiology are essential. The position is full-time, with a salary range of £37,500 to £43,350 per annum and is valid until April 30, 2028. Closing date for applications is May 17, 2026.
May 03, 2026
Full time
A leading bioscience research institute in the UK is seeking a Postdoctoral Scientist to join the FlavourFerm consortium. The successful candidate will research the influence of fermented plant-based foods on the gut microbiome and develop machine learning tools for modeling microbial communities. A PhD in a relevant field and experience in bioinformatics and microbiology are essential. The position is full-time, with a salary range of £37,500 to £43,350 per annum and is valid until April 30, 2028. Closing date for applications is May 17, 2026.
Job type: Full-time Location: Oxford, with hybrid working options available Salary: Competitive salary Right to work: You must have the right to work in the UK Application deadline: 10th April OMass Therapeutics is a biotechnology company based in Oxford discovering medicines against highly-validated target ecosystems, such as membrane proteins or intracellular complexes. The company's unique OdyssION technology platform comprises novel biochemistry techniques, next-generation native mass spectrometry and custom formatted compound libraries for ultra-high throughput screening. OMass is advancing a pipeline of small molecule therapeutics in rare diseases and immunological conditions, that target solute carriers, complex-bound proteins, and GPCRs, with biophysical platform technologies at the core of drug discovery. We are seeking a Computational Chemist. You will be part of a dynamic and innovative environment and will become an integral part of our vision to address patients' unmet needs while building Britain's Biggest Biotech. You will use your cheminformatics/computational chemistry expertise and scientific curiosity to solve drug discovery challenges, as part of multi-disciplinary project teams. You will be able to work in state-of-the-art laboratory and modern facilities for optimum collaboration alongside a focused and caring team. You will already possess expert Computational Chemistry knowledge with experience in both Ligand and Structure-Based Design with industry experience in small molecule drug discovery. Discover more about OMass and our Employee Value Proposition. Essential Experience, Skills and Qualities Ph.D. in cheminformatics/computational chemistry or equivalent industrial experience. A significant amount of relevant industry experience in small molecule drug discovery across multiple projects from hit finding to candidate selection. An appreciation of relevant scientific disciplines that are related to drug discovery and early development such as target validation, pharmacology, generative molecular design approaches, SBDD, LBDD, ADME modelling, structural biology and drug safety/toxicology. Proficiency in scientific scripting for prototyping workflows (e.g., Python, Java, C++), enabling the delivery of project specific outputs such as executing virtual screens. Proficient with classical machine/deep learning model development. Innovative and ambitious mindset, with an inquisitive and agile approach to problem-solving and overcoming technical challenges; motivated to continuously learn and take on challenges. Caring and inclusive; respectful and receptive to others' diverse ideas, experience and perspectives, and enjoys working collaboratively with others as a team. Excellent communication skills, both written and verbal. Preferred Experience and Skills Experience of working across multiple target-types including membrane bound GPCRs & solute carriers and soluble proteins. Familiarity with Dotmatics and Schrodinger software suites in addition to a sound knowledge of chemical toolkits (e.g. RDKit) is preferred. Demonstrated ability to critically assess and communicate QSAR/ machine learning model limitations, uncertainty, and suitability for program use. Experience centred on lead optimisation and later stage project cycles, with the capability to independently lead the computational elements of the design-make-test-analyse (DMTA) cycle Experience of working in a matrix team. Role Responsibilities Promote and maintain the highest levels of scientific excellence in computational chemistry, to help deliver OMass' pipeline objectives. Contribute to drug discovery projects by proactively applying cheminformatics and computational chemistry techniques to drive programs forward, providing hands on program support and scientific partnership to project teams. Support and upskill project medicinal chemists by delivering training, coaching and practical guidance in computational chemistry approaches, tools and best practices. Publish science in high quality journals and publications. Give presentations on OMass' projects both at internal meetings and externally at conferences. Foster collaborations with academia to help ensure that the team operates at the highest levels of scientific excellence. Share information openly and work collaboratively with other departments to help advance different projects and achieve company goals. Promote and adhere to OMass' values of being Ambitious, Responsible, Innovative, Focused, Caring and Collaborative. Benefits Private Health Insurance Health and wellbeing cashback scheme Life Assurance and Income Protection Participation in Employee Equity Scheme 25 days annual leave, plus bank holidays Pension Scheme offering 6% employer contribution Learning and Development Opportunities Company social events Any queries relating to the role can be sent to . OMass Therapeutics values diversity and is committed to equality of opportunity, we also have full responsibility to ensure that all employees are eligible to work and live in the UK.
May 02, 2026
Full time
Job type: Full-time Location: Oxford, with hybrid working options available Salary: Competitive salary Right to work: You must have the right to work in the UK Application deadline: 10th April OMass Therapeutics is a biotechnology company based in Oxford discovering medicines against highly-validated target ecosystems, such as membrane proteins or intracellular complexes. The company's unique OdyssION technology platform comprises novel biochemistry techniques, next-generation native mass spectrometry and custom formatted compound libraries for ultra-high throughput screening. OMass is advancing a pipeline of small molecule therapeutics in rare diseases and immunological conditions, that target solute carriers, complex-bound proteins, and GPCRs, with biophysical platform technologies at the core of drug discovery. We are seeking a Computational Chemist. You will be part of a dynamic and innovative environment and will become an integral part of our vision to address patients' unmet needs while building Britain's Biggest Biotech. You will use your cheminformatics/computational chemistry expertise and scientific curiosity to solve drug discovery challenges, as part of multi-disciplinary project teams. You will be able to work in state-of-the-art laboratory and modern facilities for optimum collaboration alongside a focused and caring team. You will already possess expert Computational Chemistry knowledge with experience in both Ligand and Structure-Based Design with industry experience in small molecule drug discovery. Discover more about OMass and our Employee Value Proposition. Essential Experience, Skills and Qualities Ph.D. in cheminformatics/computational chemistry or equivalent industrial experience. A significant amount of relevant industry experience in small molecule drug discovery across multiple projects from hit finding to candidate selection. An appreciation of relevant scientific disciplines that are related to drug discovery and early development such as target validation, pharmacology, generative molecular design approaches, SBDD, LBDD, ADME modelling, structural biology and drug safety/toxicology. Proficiency in scientific scripting for prototyping workflows (e.g., Python, Java, C++), enabling the delivery of project specific outputs such as executing virtual screens. Proficient with classical machine/deep learning model development. Innovative and ambitious mindset, with an inquisitive and agile approach to problem-solving and overcoming technical challenges; motivated to continuously learn and take on challenges. Caring and inclusive; respectful and receptive to others' diverse ideas, experience and perspectives, and enjoys working collaboratively with others as a team. Excellent communication skills, both written and verbal. Preferred Experience and Skills Experience of working across multiple target-types including membrane bound GPCRs & solute carriers and soluble proteins. Familiarity with Dotmatics and Schrodinger software suites in addition to a sound knowledge of chemical toolkits (e.g. RDKit) is preferred. Demonstrated ability to critically assess and communicate QSAR/ machine learning model limitations, uncertainty, and suitability for program use. Experience centred on lead optimisation and later stage project cycles, with the capability to independently lead the computational elements of the design-make-test-analyse (DMTA) cycle Experience of working in a matrix team. Role Responsibilities Promote and maintain the highest levels of scientific excellence in computational chemistry, to help deliver OMass' pipeline objectives. Contribute to drug discovery projects by proactively applying cheminformatics and computational chemistry techniques to drive programs forward, providing hands on program support and scientific partnership to project teams. Support and upskill project medicinal chemists by delivering training, coaching and practical guidance in computational chemistry approaches, tools and best practices. Publish science in high quality journals and publications. Give presentations on OMass' projects both at internal meetings and externally at conferences. Foster collaborations with academia to help ensure that the team operates at the highest levels of scientific excellence. Share information openly and work collaboratively with other departments to help advance different projects and achieve company goals. Promote and adhere to OMass' values of being Ambitious, Responsible, Innovative, Focused, Caring and Collaborative. Benefits Private Health Insurance Health and wellbeing cashback scheme Life Assurance and Income Protection Participation in Employee Equity Scheme 25 days annual leave, plus bank holidays Pension Scheme offering 6% employer contribution Learning and Development Opportunities Company social events Any queries relating to the role can be sent to . OMass Therapeutics values diversity and is committed to equality of opportunity, we also have full responsibility to ensure that all employees are eligible to work and live in the UK.
Key Responsibilities Define and lead a comprehensive AI strategy for Janus Henderson, continuously refining it based on emerging technologies and business needs. Lead a team of data scientists and AI engineers to develop predictive models and AI solutions, guiding the model development life cycle from proof of concept to deployment. Establish and enforce an AI governance framework, including model validation, transparency, fairness, and compliance with emerging AI regulations. Encourage collaboration across business units, embedding AI solutions into processes and supporting integration with technology teams. Monitor industry trends, evaluate new AI techniques and fintech innovations, and lead pilot programs to assess ROI and advocate for strategic investments in data science capabilities. Required Qualifications Master's or Ph.D. in Computer Science, Data Science, Statistics, Engineering, or related quantitative field. 10+ years of experience in data science or analytics, with at least 5 years in a leadership or managerial capacity, preferably in financial services or asset management. Deep expertise in machine learning and statistical modeling, hands on experience developing and deploying models (e.g., predictive models, NLP, time series forecasting) and managing model risk in a regulated environment. Solid understanding of asset management business, including investment products, portfolio management, performance analytics and regulatory compliance reporting. Demonstrated leadership and communication skills, with the ability to articulate complex analytical findings to senior executives and to influence decision making. Preferred Experience Direct experience within an asset management analytics or quantitative research team. Hands on experience establishing governance processes for AI/ML and familiarity with EU AI Act, SEC guidance on model risk and ethical AI frameworks. Proficiency with advanced analytics libraries and tools used in finance, including quantitative finance libraries, time series databases and visualization platforms such as Tableau or Power BI. Published work, patents or conference presentations related to AI or data science in finance. Technical Skills Programming: Python (pandas, scikit learn, TensorFlow/PyTorch), R, SQL, Jupyter notebooks and version control (Git). Machine Learning: regression, classification, clustering, tree based models, neural networks, MLOps practices and model deployment. Data Platforms: relational and NoSQL databases, time series stores, cloud data services (AWS Redshift, Azure Synapse, Google BigQuery) and distributed computing frameworks. Analytics & BI: Tableau, Power BI, matplotlib/Plotly, Excel or similar tools for data storytelling. AI Ethics & Security: bias detection, explainability (LIME, SHAP), data anonymization, encryption and secure data enclaves. Soft Skills & Leadership Competencies Strategic vision for AI and analytics, communicating the vision to senior leaders. High ethical standards, advocating responsible AI and refusing use cases that pose undue risk. Exceptional storytelling ability, translating complex insights into plain language for non technical audiences. Collaborative influence across IT, investment, compliance and client teams. Mentorship, fostering continuous learning and recruiting top talent. Problem solving resilience, systematically addressing data quality, model performance and resource constraints. What to Expect When You Join Hybrid working with reasonable accommodations. Generous holiday policies and paid volunteer time. Professional development support, tuition reimbursement and continuing education. All inclusive diversity, equity and inclusion culture. Maternal/paternal leave benefits and family services. Access to Headspace, ClassPass and other well being benefits. Unique employee events, including health challenges and evening socials. Supervisory Responsibilities Yes Potential for Growth Mentoring programs Leadership development Regular training sessions Career development services Continuing education courses Regulatory & Ethical Expectations You will be expected to understand the regulatory obligations of the firm and abide by JHI policies applicable to your role, including adherence to the Investment Advisory Code of Ethics. Annual Bonus Opportunity Position may be eligible for an annual discretionary bonus award from the profit pool, with individual awards based on company, department, team and personal performance. Benefits Summary Comprehensive total rewards package including competitive compensation, pension/retirement plans, health and well being benefits, and flexible work arrangements. Equal Opportunity Statement Janus Henderson Investors is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status. All applications are subject to background checks.
May 02, 2026
Full time
Key Responsibilities Define and lead a comprehensive AI strategy for Janus Henderson, continuously refining it based on emerging technologies and business needs. Lead a team of data scientists and AI engineers to develop predictive models and AI solutions, guiding the model development life cycle from proof of concept to deployment. Establish and enforce an AI governance framework, including model validation, transparency, fairness, and compliance with emerging AI regulations. Encourage collaboration across business units, embedding AI solutions into processes and supporting integration with technology teams. Monitor industry trends, evaluate new AI techniques and fintech innovations, and lead pilot programs to assess ROI and advocate for strategic investments in data science capabilities. Required Qualifications Master's or Ph.D. in Computer Science, Data Science, Statistics, Engineering, or related quantitative field. 10+ years of experience in data science or analytics, with at least 5 years in a leadership or managerial capacity, preferably in financial services or asset management. Deep expertise in machine learning and statistical modeling, hands on experience developing and deploying models (e.g., predictive models, NLP, time series forecasting) and managing model risk in a regulated environment. Solid understanding of asset management business, including investment products, portfolio management, performance analytics and regulatory compliance reporting. Demonstrated leadership and communication skills, with the ability to articulate complex analytical findings to senior executives and to influence decision making. Preferred Experience Direct experience within an asset management analytics or quantitative research team. Hands on experience establishing governance processes for AI/ML and familiarity with EU AI Act, SEC guidance on model risk and ethical AI frameworks. Proficiency with advanced analytics libraries and tools used in finance, including quantitative finance libraries, time series databases and visualization platforms such as Tableau or Power BI. Published work, patents or conference presentations related to AI or data science in finance. Technical Skills Programming: Python (pandas, scikit learn, TensorFlow/PyTorch), R, SQL, Jupyter notebooks and version control (Git). Machine Learning: regression, classification, clustering, tree based models, neural networks, MLOps practices and model deployment. Data Platforms: relational and NoSQL databases, time series stores, cloud data services (AWS Redshift, Azure Synapse, Google BigQuery) and distributed computing frameworks. Analytics & BI: Tableau, Power BI, matplotlib/Plotly, Excel or similar tools for data storytelling. AI Ethics & Security: bias detection, explainability (LIME, SHAP), data anonymization, encryption and secure data enclaves. Soft Skills & Leadership Competencies Strategic vision for AI and analytics, communicating the vision to senior leaders. High ethical standards, advocating responsible AI and refusing use cases that pose undue risk. Exceptional storytelling ability, translating complex insights into plain language for non technical audiences. Collaborative influence across IT, investment, compliance and client teams. Mentorship, fostering continuous learning and recruiting top talent. Problem solving resilience, systematically addressing data quality, model performance and resource constraints. What to Expect When You Join Hybrid working with reasonable accommodations. Generous holiday policies and paid volunteer time. Professional development support, tuition reimbursement and continuing education. All inclusive diversity, equity and inclusion culture. Maternal/paternal leave benefits and family services. Access to Headspace, ClassPass and other well being benefits. Unique employee events, including health challenges and evening socials. Supervisory Responsibilities Yes Potential for Growth Mentoring programs Leadership development Regular training sessions Career development services Continuing education courses Regulatory & Ethical Expectations You will be expected to understand the regulatory obligations of the firm and abide by JHI policies applicable to your role, including adherence to the Investment Advisory Code of Ethics. Annual Bonus Opportunity Position may be eligible for an annual discretionary bonus award from the profit pool, with individual awards based on company, department, team and personal performance. Benefits Summary Comprehensive total rewards package including competitive compensation, pension/retirement plans, health and well being benefits, and flexible work arrangements. Equal Opportunity Statement Janus Henderson Investors is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status. All applications are subject to background checks.
A leading UK university in Glasgow seeks a Researcher to contribute to an important project on cyclic peptide aptamers using AI and machine learning. Key responsibilities include leading research, documenting findings, and securing funding. Essential qualifications include a PhD and expertise in mRNA display technologies. The role offers a competitive salary of £41,064 to £46,049 and focuses on enhancing research impact and collaboration within the academic community.
May 01, 2026
Full time
A leading UK university in Glasgow seeks a Researcher to contribute to an important project on cyclic peptide aptamers using AI and machine learning. Key responsibilities include leading research, documenting findings, and securing funding. Essential qualifications include a PhD and expertise in mRNA display technologies. The role offers a competitive salary of £41,064 to £46,049 and focuses on enhancing research impact and collaboration within the academic community.
Overview At the Ellison Institute of Technology (EIT), we're on a mission to translate scientific discovery into real world impact. We bring together visionary scientists, technologists, engineers, researchers, educators and innovators to tackle humanity's greatest challenges in four transformative areas: Health, Medical Science & Generative Biology Food Security & Sustainable Agriculture Climate Change & Managing CO Artificial Intelligence & Robotics This is ambitious work - work that demands curiosity, courage, and a relentless drive to make a difference. At EIT, you'll join a community built on excellence, innovation, tenacity, trust, and collaboration, where bold ideas become real-world breakthroughs. Explore more at . Welcome to the Pathogen Project: Within this ecosystem, the Pathogen Project exemplifies EIT's dedication to ground-breaking science. It seeks to transform pathogen risk management, detection and response by leveraging Whole Genome Sequencing (WGS)-based metagenomic and pathogen-specific analytical tools. The goal is to power metagenomic devices using long-read sequencing technologies by building a comprehensive database of pathogen information to inform response. Enabled by Oracle Inc.'s cloud-computing scale and security, the Pathogen Project is advancing toward certified diagnostic tools for deployment in laboratories, hospitals, and public health organisations worldwide. Your Role: At EIT we are seeking an experienced and detailed orientated (Senior or Non Senior) Scientist with recognised expertise in developing computational methods and algorithms for genomic sequencing data analysis. This is an exciting opportunity to develop novel computational approaches for microbial data that will become part of our diagnostic products and thus help shape the future of infectious disease diagnostics. Reporting to the Lead Scientist in Computational Genomics, you will work closely with computational scientists, bioinformaticians, software engineers, and our database and data platform teams to deliver scientifically rigorous, scalable, and clinically relevant innovation in the microbial genomics space. Key Responsibilities: Design, develop and evaluate novel computational approaches in areas such as genome assembly, binning, and functional characterisation of genomes from metagenomic sequencing data Collaborate with scientists across EIT to apply the latest developments in AI/ML to real-world challenges in the pathogen space Work with bioinformaticians and software engineers to implement methods in scalable, reproducible, and modular workflows Perform rigorous benchmarking using public and internal datasets, and guide experimental validation efforts in collaboration with our wet-lab teams Communicate technical concepts to broad audiences and collaborate with interdisciplinary colleagues across the organisation Essential Knowledge, Skills and Experience: PhD or equivalent experience in bioinformatics, computational biology, computer science, or a related quantitative field Senior: At least 3 years of postdoctoral or industry experience developing computational methods for next-generation sequencing data Non-Senior: Hands-on experience developing computational methods for next-generation sequencing data Significant experience with bioinformatics methods such as efficient search and storage of DNA sequences, genome assembly, genome annotation, pangenomes, phylogenetics, and comparative genomics Solid understanding of data structures, algorithms, and statistical methods (e.g. De Bruijn graphs, hashing, Burrows-Wheeler transform, Bayesian methods, mixed models, dimensionality reduction, embeddings) Experience with machine learning in the context of biological data, particularly sequencing data Proficient in the use of command-line interfaces, low and high-level programming languages (e.g. Python, C, C++, Rust) and modern software development techniques (version control, CI/CD) Track record of scientific output and engagement with the computational genomics community Desirable Knowledge, Skills and Experience: Experience working with microbial genomes and shotgun metagenomics data Experience working with long-read sequencing data (ONT) Experience with bioinformatics workflow management (e.g. Nextflow) and cloud computing (e.g. OCI, AWS, GCP) Contributions to open-source bioinformatics software Previous experience mentoring or line-managing scientists (For Senior) Key Attributes: Strategic thinker with the ability to translate scientific insights into practical solutions Effective communicator and enthusiastic knowledge sharer across disciplines Rigorous and detail-oriented with a commitment to reproducibility and benchmarking Comfortable in a fast-paced, interdisciplinary environment and able to adapt to evolving priorities Collaborative ethos with the ability to work across teams and domains Our Benefits: Salary: Competitive + travel allowance + bonus Enhanced holiday + options to buy additional days Pension Life Assurance Income Protection Private Medical Insurance Hospital Cash Plan Therapy Services Perk Box Electric Car Scheme Childcare benefit Working Together - What It Involves: You must have the permanent right to work in the UK and be willing to travel when required. Given the specialised nature of this role, we can consider sponsorship for candidates who meet the expectations outlined in the job description. You will live in, or within easy commuting distance of, Oxford (or be willing to relocate).
May 01, 2026
Full time
Overview At the Ellison Institute of Technology (EIT), we're on a mission to translate scientific discovery into real world impact. We bring together visionary scientists, technologists, engineers, researchers, educators and innovators to tackle humanity's greatest challenges in four transformative areas: Health, Medical Science & Generative Biology Food Security & Sustainable Agriculture Climate Change & Managing CO Artificial Intelligence & Robotics This is ambitious work - work that demands curiosity, courage, and a relentless drive to make a difference. At EIT, you'll join a community built on excellence, innovation, tenacity, trust, and collaboration, where bold ideas become real-world breakthroughs. Explore more at . Welcome to the Pathogen Project: Within this ecosystem, the Pathogen Project exemplifies EIT's dedication to ground-breaking science. It seeks to transform pathogen risk management, detection and response by leveraging Whole Genome Sequencing (WGS)-based metagenomic and pathogen-specific analytical tools. The goal is to power metagenomic devices using long-read sequencing technologies by building a comprehensive database of pathogen information to inform response. Enabled by Oracle Inc.'s cloud-computing scale and security, the Pathogen Project is advancing toward certified diagnostic tools for deployment in laboratories, hospitals, and public health organisations worldwide. Your Role: At EIT we are seeking an experienced and detailed orientated (Senior or Non Senior) Scientist with recognised expertise in developing computational methods and algorithms for genomic sequencing data analysis. This is an exciting opportunity to develop novel computational approaches for microbial data that will become part of our diagnostic products and thus help shape the future of infectious disease diagnostics. Reporting to the Lead Scientist in Computational Genomics, you will work closely with computational scientists, bioinformaticians, software engineers, and our database and data platform teams to deliver scientifically rigorous, scalable, and clinically relevant innovation in the microbial genomics space. Key Responsibilities: Design, develop and evaluate novel computational approaches in areas such as genome assembly, binning, and functional characterisation of genomes from metagenomic sequencing data Collaborate with scientists across EIT to apply the latest developments in AI/ML to real-world challenges in the pathogen space Work with bioinformaticians and software engineers to implement methods in scalable, reproducible, and modular workflows Perform rigorous benchmarking using public and internal datasets, and guide experimental validation efforts in collaboration with our wet-lab teams Communicate technical concepts to broad audiences and collaborate with interdisciplinary colleagues across the organisation Essential Knowledge, Skills and Experience: PhD or equivalent experience in bioinformatics, computational biology, computer science, or a related quantitative field Senior: At least 3 years of postdoctoral or industry experience developing computational methods for next-generation sequencing data Non-Senior: Hands-on experience developing computational methods for next-generation sequencing data Significant experience with bioinformatics methods such as efficient search and storage of DNA sequences, genome assembly, genome annotation, pangenomes, phylogenetics, and comparative genomics Solid understanding of data structures, algorithms, and statistical methods (e.g. De Bruijn graphs, hashing, Burrows-Wheeler transform, Bayesian methods, mixed models, dimensionality reduction, embeddings) Experience with machine learning in the context of biological data, particularly sequencing data Proficient in the use of command-line interfaces, low and high-level programming languages (e.g. Python, C, C++, Rust) and modern software development techniques (version control, CI/CD) Track record of scientific output and engagement with the computational genomics community Desirable Knowledge, Skills and Experience: Experience working with microbial genomes and shotgun metagenomics data Experience working with long-read sequencing data (ONT) Experience with bioinformatics workflow management (e.g. Nextflow) and cloud computing (e.g. OCI, AWS, GCP) Contributions to open-source bioinformatics software Previous experience mentoring or line-managing scientists (For Senior) Key Attributes: Strategic thinker with the ability to translate scientific insights into practical solutions Effective communicator and enthusiastic knowledge sharer across disciplines Rigorous and detail-oriented with a commitment to reproducibility and benchmarking Comfortable in a fast-paced, interdisciplinary environment and able to adapt to evolving priorities Collaborative ethos with the ability to work across teams and domains Our Benefits: Salary: Competitive + travel allowance + bonus Enhanced holiday + options to buy additional days Pension Life Assurance Income Protection Private Medical Insurance Hospital Cash Plan Therapy Services Perk Box Electric Car Scheme Childcare benefit Working Together - What It Involves: You must have the permanent right to work in the UK and be willing to travel when required. Given the specialised nature of this role, we can consider sponsorship for candidates who meet the expectations outlined in the job description. You will live in, or within easy commuting distance of, Oxford (or be willing to relocate).
Overview The Head of Data Science & AI spearheads Janus Henderson's data driven initiatives, leading the development and execution of a strategy that harnesses data and artificial intelligence across the organization. The role oversees advanced analytics, AI model development, and AI/ML governance, ensuring that AI is applied ethically and effectively to enhance investment research, client experience, and operations while maintaining the firm's standards of accuracy, transparency, and trust. Key Responsibilities AI Strategy: Define and lead a comprehensive AI strategy aligned with business objectives, continuously refining it based on emerging technologies and evolving needs. Model Development & AI Innovation: Lead a team of data scientists and AI engineers to develop predictive models and AI solutions, guiding the model lifecycle from proof of concept to production and ensuring ongoing value and maintenance. AI Governance & Ethics: Establish and enforce an AI governance framework, including model validation, transparency, fairness, and compliance with emerging AI regulations. Enablement & Collaboration: Act as a bridge between the Data Science team and other business units, fostering integration of AI solutions into processes and working closely with technology leaders. Emerging Technology & Thought Leadership: Monitor industry trends, evaluate new AI techniques, pilot innovations, and advocate for investments that deliver competitive advantage and risk reduction. Required Qualifications Education: Master's or Ph.D. in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field. Experience: 10+ years in data science, analytics, or related technology roles, with a minimum of 5 years in leadership or managerial capacity. Experience in financial services, asset management, or capital markets is highly desirable. Technical Proficiency: Deep expertise in machine learning techniques, statistical modeling, and large dataset analytics; proven track record of model development and deployment. Industry Knowledge: Solid understanding of asset management products, portfolio management, performance analytics, and client servicing; awareness of how AI is applied in investment management. Leadership & Communication: Demonstrated ability to lead multidisciplinary teams, manage complex projects, and convey analytical insights to senior executives. Preferred Experience Direct experience in an asset management analytics or quantitative research team. Established AI/ML governance processes, including model review committees and monitoring frameworks. Familiarity with advanced analytics ecosystems in finance (e.g., quantitative libraries, time series databases, visualization tools). Published research, patents, or conference presentations in AI or data science related to finance. Technical Skills Programming: Python (pandas, scikit learn, TensorFlow/PyTorch), R, SQL, notebooks, Git. Machine Learning: regression, classification, clustering, tree based models, neural networks; MLOps, model deployment, automated testing. Data Platforms: relational databases, NoSQL, time series, big data frameworks, cloud data services (AWS, Azure, GCP). Analytics & BI: Tableau, Power BI, Python/R visualization, statistical analysis tools. AI Ethics & Security: bias detection, explainability (LIME, SHAP), data anonymization, encryption. Soft Skills & Leadership Competencies Strategic Vision & Innovation Ethical Leadership & Responsible AI advocacy Storytelling & Communication for non technical audiences Collaboration & Influence across organizational boundaries Mentorship & Talent Development Problem Solving & Resilience Benefits and Working Conditions Hybrid working environment with reasonable accommodations Generous holiday policy Paid volunteer time Professional development support (courses, tuition reimbursement) Inclusive diversity, equity, and inclusion initiatives Family leave benefits Well being initiatives (Headspace, ClassPass) Employee events and wellness perks (complimentary beverages, happy hours) Janus Henderson is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status. All applications are subject to background checks. Applicants must comply with the firm's Investment Advisory Code of Ethics and any relevant regulatory obligations.
May 01, 2026
Full time
Overview The Head of Data Science & AI spearheads Janus Henderson's data driven initiatives, leading the development and execution of a strategy that harnesses data and artificial intelligence across the organization. The role oversees advanced analytics, AI model development, and AI/ML governance, ensuring that AI is applied ethically and effectively to enhance investment research, client experience, and operations while maintaining the firm's standards of accuracy, transparency, and trust. Key Responsibilities AI Strategy: Define and lead a comprehensive AI strategy aligned with business objectives, continuously refining it based on emerging technologies and evolving needs. Model Development & AI Innovation: Lead a team of data scientists and AI engineers to develop predictive models and AI solutions, guiding the model lifecycle from proof of concept to production and ensuring ongoing value and maintenance. AI Governance & Ethics: Establish and enforce an AI governance framework, including model validation, transparency, fairness, and compliance with emerging AI regulations. Enablement & Collaboration: Act as a bridge between the Data Science team and other business units, fostering integration of AI solutions into processes and working closely with technology leaders. Emerging Technology & Thought Leadership: Monitor industry trends, evaluate new AI techniques, pilot innovations, and advocate for investments that deliver competitive advantage and risk reduction. Required Qualifications Education: Master's or Ph.D. in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field. Experience: 10+ years in data science, analytics, or related technology roles, with a minimum of 5 years in leadership or managerial capacity. Experience in financial services, asset management, or capital markets is highly desirable. Technical Proficiency: Deep expertise in machine learning techniques, statistical modeling, and large dataset analytics; proven track record of model development and deployment. Industry Knowledge: Solid understanding of asset management products, portfolio management, performance analytics, and client servicing; awareness of how AI is applied in investment management. Leadership & Communication: Demonstrated ability to lead multidisciplinary teams, manage complex projects, and convey analytical insights to senior executives. Preferred Experience Direct experience in an asset management analytics or quantitative research team. Established AI/ML governance processes, including model review committees and monitoring frameworks. Familiarity with advanced analytics ecosystems in finance (e.g., quantitative libraries, time series databases, visualization tools). Published research, patents, or conference presentations in AI or data science related to finance. Technical Skills Programming: Python (pandas, scikit learn, TensorFlow/PyTorch), R, SQL, notebooks, Git. Machine Learning: regression, classification, clustering, tree based models, neural networks; MLOps, model deployment, automated testing. Data Platforms: relational databases, NoSQL, time series, big data frameworks, cloud data services (AWS, Azure, GCP). Analytics & BI: Tableau, Power BI, Python/R visualization, statistical analysis tools. AI Ethics & Security: bias detection, explainability (LIME, SHAP), data anonymization, encryption. Soft Skills & Leadership Competencies Strategic Vision & Innovation Ethical Leadership & Responsible AI advocacy Storytelling & Communication for non technical audiences Collaboration & Influence across organizational boundaries Mentorship & Talent Development Problem Solving & Resilience Benefits and Working Conditions Hybrid working environment with reasonable accommodations Generous holiday policy Paid volunteer time Professional development support (courses, tuition reimbursement) Inclusive diversity, equity, and inclusion initiatives Family leave benefits Well being initiatives (Headspace, ClassPass) Employee events and wellness perks (complimentary beverages, happy hours) Janus Henderson is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status. All applications are subject to background checks. Applicants must comply with the firm's Investment Advisory Code of Ethics and any relevant regulatory obligations.
White Collar Factory (95009), United Kingdom, London, London Engineering Manager - Software & ML About this role We are looking for a Software Engineering Manager who brings a solid foundation in modern development and some experience with Machine Learning environments . You'll lead and grow a team that builds the core software powering our data-driven financial products, ensuring our models are integrated into seamless, consumer-facing experiences. What you'll do Lead & Scale: Support a cross-functional group of engineers to design, develop, and integrate software features that are vital to the lives of credit card consumers. Nurture Talent: Coach and nurture your engineers, including those working on ML integration to achieve their technical, business, and personal goals. Bridge the Gap: Collaborate with Product Managers and Data Scientists to ensure ML models are effectively integrated into our production software. Build Robust Systems: Oversee the development of platforms that are performant, secure, and capable of handling the unique deployment needs of AI-powered features. Optimize Delivery: Enhance engineering and agile processes, ensuring that model updates and software releases move in sync. What we're looking for Leadership Excellence: Proven experience leading and supporting software engineering teams to achieve business goals. Technical Breadth: Excellent knowledge of RESTful API development in modern languages (Java, Python, or .Net) and experience with Cloud environments (AWS or Azure). AI Awareness: You aren't necessarily a researcher, but you have expectations of how AI fits into the stack . You understand the basics of model inference, data requirements, and how to manage the non-deterministic nature of AI. Strategic Thinking: Comfortable making technical trade-offs between the need for rapid experimentation and long-term architectural stability. Collaborative Mindset: Ability to communicate effectively across engineering teams to maximize inner-sourcing and reduce technical debt. What you'll get to learn ML Integration at Scale: How to take machine learning models out of the lab and into a high-concurrency production environment. Regulated AI: Navigating the complexities of fairness and transparency in a regulated financial landscape. Cloud Evolution: Deepening your expertise in AWS/Cloud native tools that support modern intelligent applications. Where and how you'll work This is a permanent position based in either our London or Nottingham offices. We have a hybrid working model. You'll be based in the office 3 days a week (Tuesdays, Wednesdays, and Thursdays) to foster team connection and collaboration. What's in it for you Innovation Time: We give you 10% of your time to work on cutting-edge projects-whether that's exploring new AI frameworks or building internal tools. Growth: Access to Capital One University and external training to help you grow as both a leader and a technical strategist. Total Reward: Competitive salary, performance bonus, and immediate access to core benefits (pension, private medical, and generous holiday). World-Class Facilities: From our Nottingham gym and music rooms to our London rooftop running track and premium coffee bars. Our Commitment to Diversity We pride ourselves on hiring the best people, not the same people. We partner with organisations like Women in Tech and Stonewall to ensure we build teams that reflect the customers we serve. We offer a host of internal networks including REACH (Race Equality and Culture Heritage), OutFront (LGBTQ+ support), and Mind Your Mind . Capital One is committed to diversity in the workplace. If you require a reasonable adjustment, please contact All information will be kept confidential and will only be used for the purpose of applying a reasonable adjustment. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC). Who We Are At Capital One, we're building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding. Guided by our shared values, we thrive in an environment where collaboration and openness are valued. We believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. We elevate each other and obsess about doing the right thing. Our associates serve with humility and a deep respect for their responsibility in helping our customers achieve their goals and realize their dreams. Together, we are on a quest to change banking for good.
Apr 30, 2026
Full time
White Collar Factory (95009), United Kingdom, London, London Engineering Manager - Software & ML About this role We are looking for a Software Engineering Manager who brings a solid foundation in modern development and some experience with Machine Learning environments . You'll lead and grow a team that builds the core software powering our data-driven financial products, ensuring our models are integrated into seamless, consumer-facing experiences. What you'll do Lead & Scale: Support a cross-functional group of engineers to design, develop, and integrate software features that are vital to the lives of credit card consumers. Nurture Talent: Coach and nurture your engineers, including those working on ML integration to achieve their technical, business, and personal goals. Bridge the Gap: Collaborate with Product Managers and Data Scientists to ensure ML models are effectively integrated into our production software. Build Robust Systems: Oversee the development of platforms that are performant, secure, and capable of handling the unique deployment needs of AI-powered features. Optimize Delivery: Enhance engineering and agile processes, ensuring that model updates and software releases move in sync. What we're looking for Leadership Excellence: Proven experience leading and supporting software engineering teams to achieve business goals. Technical Breadth: Excellent knowledge of RESTful API development in modern languages (Java, Python, or .Net) and experience with Cloud environments (AWS or Azure). AI Awareness: You aren't necessarily a researcher, but you have expectations of how AI fits into the stack . You understand the basics of model inference, data requirements, and how to manage the non-deterministic nature of AI. Strategic Thinking: Comfortable making technical trade-offs between the need for rapid experimentation and long-term architectural stability. Collaborative Mindset: Ability to communicate effectively across engineering teams to maximize inner-sourcing and reduce technical debt. What you'll get to learn ML Integration at Scale: How to take machine learning models out of the lab and into a high-concurrency production environment. Regulated AI: Navigating the complexities of fairness and transparency in a regulated financial landscape. Cloud Evolution: Deepening your expertise in AWS/Cloud native tools that support modern intelligent applications. Where and how you'll work This is a permanent position based in either our London or Nottingham offices. We have a hybrid working model. You'll be based in the office 3 days a week (Tuesdays, Wednesdays, and Thursdays) to foster team connection and collaboration. What's in it for you Innovation Time: We give you 10% of your time to work on cutting-edge projects-whether that's exploring new AI frameworks or building internal tools. Growth: Access to Capital One University and external training to help you grow as both a leader and a technical strategist. Total Reward: Competitive salary, performance bonus, and immediate access to core benefits (pension, private medical, and generous holiday). World-Class Facilities: From our Nottingham gym and music rooms to our London rooftop running track and premium coffee bars. Our Commitment to Diversity We pride ourselves on hiring the best people, not the same people. We partner with organisations like Women in Tech and Stonewall to ensure we build teams that reflect the customers we serve. We offer a host of internal networks including REACH (Race Equality and Culture Heritage), OutFront (LGBTQ+ support), and Mind Your Mind . Capital One is committed to diversity in the workplace. If you require a reasonable adjustment, please contact All information will be kept confidential and will only be used for the purpose of applying a reasonable adjustment. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC). Who We Are At Capital One, we're building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding. Guided by our shared values, we thrive in an environment where collaboration and openness are valued. We believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. We elevate each other and obsess about doing the right thing. Our associates serve with humility and a deep respect for their responsibility in helping our customers achieve their goals and realize their dreams. Together, we are on a quest to change banking for good.
DevOps Engineer Senior or Mid Level Role: DevOps Engineer or Senior DevOps Engineer (Flexible Seniority) Security Clearance: Current DV Clearance Required (eDV Eligibility Essential) Location: Central London (Hybrid - Maximum 3 days in office) Salary: 50,000 - 85,000 (D.O.E) I am currently partnering with an elite technical consultancy that operates at the mission-critical intersection of AI, Data Science, and National Security . My client is looking for a DV-cleared DevOps specialist to join a division dedicated to solving high-stakes challenges that drive genuine societal change. This is a rare opportunity for a cleared professional to step out of "legacy" environments and work with a modern tech stack-including AI infrastructure and cloud-native automation -within a culture that offers a maximum 3-day office presence. The Choice is Yours: Engineer or Senior? My client prioritizes the right mindset and clearance level over a specific number of years on a CV. They are open to meeting candidates at two levels: Engineer ( 50k - 65k): You'll be the engine room of the deployment cycle-building robust CI/CD pipelines, automating AWS environments, and ensuring high-availability for complex AI solutions. Senior Engineer ( 65k - 85k): You will take a "player-coach" approach-architecting bespoke infrastructure, mentoring rising talent, and challenging existing orthodoxies to shape the firm's long-term engineering roadmap. The Tech Challenge Working in highly collaborative, cleared squads alongside Software Engineers and Data Scientists, you will: Automate AI Workflows: Design and deploy infrastructure for AI and Machine Learning solutions tailored for secure, restricted client environments. Scale AWS Environments: Leverage Terraform, Kubernetes, and GitOps to manage complex, highly-restricted infrastructures. Drive Operational Excellence: Act as the pivotal link between technical delivery and mission-critical requirements, ensuring solutions are robust, compliant, and cutting-edge. What You'll Bring To be successful in this process, you will need: Clearance: You must currently hold DV Clearance and be eligible for eDV . Technical Foundations: Proven experience with AWS, Docker, and Git. Infrastructure as Code: A solid grip on Terraform and/or Kubernetes. Agile Mindset: You thrive in fast-paced environments and can navigate change effectively. Software Awareness: Knowledge of the dev lifecycle (TypeScript, Node.js, or SQL) is a major advantage. Apply now for a confidential discussion regarding the role, the client, and their 2026 project roadmap.
Apr 30, 2026
Full time
DevOps Engineer Senior or Mid Level Role: DevOps Engineer or Senior DevOps Engineer (Flexible Seniority) Security Clearance: Current DV Clearance Required (eDV Eligibility Essential) Location: Central London (Hybrid - Maximum 3 days in office) Salary: 50,000 - 85,000 (D.O.E) I am currently partnering with an elite technical consultancy that operates at the mission-critical intersection of AI, Data Science, and National Security . My client is looking for a DV-cleared DevOps specialist to join a division dedicated to solving high-stakes challenges that drive genuine societal change. This is a rare opportunity for a cleared professional to step out of "legacy" environments and work with a modern tech stack-including AI infrastructure and cloud-native automation -within a culture that offers a maximum 3-day office presence. The Choice is Yours: Engineer or Senior? My client prioritizes the right mindset and clearance level over a specific number of years on a CV. They are open to meeting candidates at two levels: Engineer ( 50k - 65k): You'll be the engine room of the deployment cycle-building robust CI/CD pipelines, automating AWS environments, and ensuring high-availability for complex AI solutions. Senior Engineer ( 65k - 85k): You will take a "player-coach" approach-architecting bespoke infrastructure, mentoring rising talent, and challenging existing orthodoxies to shape the firm's long-term engineering roadmap. The Tech Challenge Working in highly collaborative, cleared squads alongside Software Engineers and Data Scientists, you will: Automate AI Workflows: Design and deploy infrastructure for AI and Machine Learning solutions tailored for secure, restricted client environments. Scale AWS Environments: Leverage Terraform, Kubernetes, and GitOps to manage complex, highly-restricted infrastructures. Drive Operational Excellence: Act as the pivotal link between technical delivery and mission-critical requirements, ensuring solutions are robust, compliant, and cutting-edge. What You'll Bring To be successful in this process, you will need: Clearance: You must currently hold DV Clearance and be eligible for eDV . Technical Foundations: Proven experience with AWS, Docker, and Git. Infrastructure as Code: A solid grip on Terraform and/or Kubernetes. Agile Mindset: You thrive in fast-paced environments and can navigate change effectively. Software Awareness: Knowledge of the dev lifecycle (TypeScript, Node.js, or SQL) is a major advantage. Apply now for a confidential discussion regarding the role, the client, and their 2026 project roadmap.
Senior Data Scientist Location: London (Hybrid) | Practice Area : Data & Analytics | Type: Permanent Shape intelligent solutions. Lead with insight. Drive data innovation. The Role We are looking for a Senior Data Scientist to join Capco's growing UK Data Practice. You will play a leading role in designing and implementing cutting-edge data science solutions across financial services. This is an opportunity to build intelligent systems that drive commercial and customer outcomes - while mentoring others and collaborating in a dynamic, multi-disciplinary environment. What You'll Do Lead the end-to-end delivery of data science solutions including PoCs, MVPs and production deployments Develop and prototype ML models to solve complex business challenges using modern techniques and tooling Collaborate closely with engineers, domain experts, and business teams to translate requirements into deliverables Guide and coach data science pods, supporting skill development and solution design Act as a subject matter expert on ML architecture, model calibration and productionisation What We're Looking For Hands-on experience building and deploying data science solutions in Python and related ML libraries Strong background in applied machine learning, model development and data engineering Experience with cloud environments (Azure, AWS, GCP) and tools such as Spark, Hive, Redshift Demonstrated ability to lead cross-functional teams and mentor junior practitioners Ability to communicate complex technical concepts clearly to non-technical audiences Bonus Points For Participation in Kaggle or other data science competitions Experience with MLOps practices (CI/CD, model monitoring, DevOps integration) Familiarity with advanced NLP frameworks such as spaCy or Transformers MSc or PhD in a numerate discipline Financial services or banking experience Why Join Capco Deliver high-impact technology solutions for Tier 1 financial institutions Work in a collaborative, flat, and entrepreneurial consulting culture Access continuous learning, training, and industry certifications Be part of a team shaping the future of digital financial services Help shape the future of digital transformation across FS & Energy. We offer a competitive, people-first benefits package designed to support every aspect of your life: Core Benefits: Discretionary bonus, competitive pension, health insurance, life insurance and critical illness cover. Mental Health: Easy access to CareFirst, Unmind, Aviva consultations and in-house first aiders. Family-Friendly: Maternity, adoption, shared parental leave, plus paid leave for sickness, pregnancy loss, fertility treatment, menopause and bereavement. Family Care: 8 complimentary backup care sessions for emergency childcare or elder care. Holiday Flexibility: 5 weeks of annual leave with the option to buy or sell holiday days based on your needs. Continuous Learning: Minimum 40 Hours of Training Annually: Take your pick - workshops, certifications, E-learning - your growth, your way. Also, Business Coach assigned from Day One: Get one-on-one guidance to fast-track your goals and accelerate your development. Healthcare Access: Convenient online GP services. Extra Perks: Gympass (Wellhub), travel insurance, Tastecard, season ticket loans, Cycle to Work and dental insurance. Inclusion at Capco We're committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know - we'll be happy to help. We value each person's unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our culture encourages individuality and collaboration - a mindset that shapes how we work with clients and each other every day.
Apr 30, 2026
Full time
Senior Data Scientist Location: London (Hybrid) | Practice Area : Data & Analytics | Type: Permanent Shape intelligent solutions. Lead with insight. Drive data innovation. The Role We are looking for a Senior Data Scientist to join Capco's growing UK Data Practice. You will play a leading role in designing and implementing cutting-edge data science solutions across financial services. This is an opportunity to build intelligent systems that drive commercial and customer outcomes - while mentoring others and collaborating in a dynamic, multi-disciplinary environment. What You'll Do Lead the end-to-end delivery of data science solutions including PoCs, MVPs and production deployments Develop and prototype ML models to solve complex business challenges using modern techniques and tooling Collaborate closely with engineers, domain experts, and business teams to translate requirements into deliverables Guide and coach data science pods, supporting skill development and solution design Act as a subject matter expert on ML architecture, model calibration and productionisation What We're Looking For Hands-on experience building and deploying data science solutions in Python and related ML libraries Strong background in applied machine learning, model development and data engineering Experience with cloud environments (Azure, AWS, GCP) and tools such as Spark, Hive, Redshift Demonstrated ability to lead cross-functional teams and mentor junior practitioners Ability to communicate complex technical concepts clearly to non-technical audiences Bonus Points For Participation in Kaggle or other data science competitions Experience with MLOps practices (CI/CD, model monitoring, DevOps integration) Familiarity with advanced NLP frameworks such as spaCy or Transformers MSc or PhD in a numerate discipline Financial services or banking experience Why Join Capco Deliver high-impact technology solutions for Tier 1 financial institutions Work in a collaborative, flat, and entrepreneurial consulting culture Access continuous learning, training, and industry certifications Be part of a team shaping the future of digital financial services Help shape the future of digital transformation across FS & Energy. We offer a competitive, people-first benefits package designed to support every aspect of your life: Core Benefits: Discretionary bonus, competitive pension, health insurance, life insurance and critical illness cover. Mental Health: Easy access to CareFirst, Unmind, Aviva consultations and in-house first aiders. Family-Friendly: Maternity, adoption, shared parental leave, plus paid leave for sickness, pregnancy loss, fertility treatment, menopause and bereavement. Family Care: 8 complimentary backup care sessions for emergency childcare or elder care. Holiday Flexibility: 5 weeks of annual leave with the option to buy or sell holiday days based on your needs. Continuous Learning: Minimum 40 Hours of Training Annually: Take your pick - workshops, certifications, E-learning - your growth, your way. Also, Business Coach assigned from Day One: Get one-on-one guidance to fast-track your goals and accelerate your development. Healthcare Access: Convenient online GP services. Extra Perks: Gympass (Wellhub), travel insurance, Tastecard, season ticket loans, Cycle to Work and dental insurance. Inclusion at Capco We're committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know - we'll be happy to help. We value each person's unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our culture encourages individuality and collaboration - a mindset that shapes how we work with clients and each other every day.
Data Science Manager page is loaded Data Science Managerremote type: Hybridlocations: Belfast - 20 Adelaide Streetposted on: Posted Todayjob requisition id: JR-Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation and navigate constant change. Through a combination of strategy, expertise and creativity, we help clients accelerate operational, digital and cultural transformation, enabling the change they need to own their future. Join our team as the expert you are now and create your future. Data Science Manager We're seeking a Data Science Manager to join the Data Science & Machine Learning team in our Commercial Digital practice, where you'll lead advanced analytics initiatives that transform how Fortune 500 companies make decisions across Financial Services, Manufacturing, Energy & Utilities, and other commercial industries.Managers play a vibrant, integral role at Huron. Their invaluable knowledge reflects in the projects they manage and the teams they lead. Known for building long-standing partnerships with clients, they collaborate with colleagues to solve their most important challenges. Our Managers also spend significant time mentoring junior staff on the engagement team-sharing expertise, feedback, and encouragement. This promotes a culture of respect, unity, collaboration, and personal achievement.This isn't a reporting role or a dashboard factory-you'll own the full analytics lifecycle from hypothesis formulation through insight delivery, while leading and developing a team of data scientists and analysts. You'll work on problems that matter: experimental designs that validate multi-million-dollar strategies, predictive models that surface hidden patterns in complex data, and deep learning pipelines that extract signal from unstructured text, images, and time-series. Our clients are Fortune 500 companies looking for partners who can find the signal in the noise and tell the story that drives action.The variety is real. In your first year, you might lead a customer segmentation and lifetime value analysis for a financial services firm, design and analyze a pricing experiment for a global manufacturer, and build an agentic anomaly detection system for a utility company's operational data-all while developing the next generation of data science talent at Huron. If you thrive on rigorous analysis, clear communication of complex findings, and building high-performing teams, this role is for you.# What You'll Do Lead and mentor junior data scientists and analysts -provide technical guidance, review analytical approaches and code, and support professional development. Foster a culture of intellectual curiosity, rigorous methodology, and clear communication within the team. Manage complex multi-workstream analytics projects -oversee project planning, resource allocation, and delivery timelines. Ensure analyses meet quality standards and client expectations while maintaining methodological rigor. Design and execute end-to-end data science workflows -from problem framing and hypothesis development through exploratory analysis, modeling, validation, and insight delivery. Own the analytical approach and ensure conclusions are defensible. Lead development of both traditional statistical and modern AI-powered analyses -including regression, classification, clustering, causal inference, A/B testing, and modern deep learning approaches using embeddings, transformer architectures, and foundation models for text, time-series, and multimodal analysis. Build predictive and prescriptive models that drive business decisions-customer segmentation, churn prediction, demand forecasting, pricing optimization, risk scoring, and operational efficiency analysis for commercial enterprises. Translate complex analytical findings into actionable insights -create compelling data narratives, develop executive-ready presentations, and communicate technical results to non-technical stakeholders in ways that drive decisions. Serve as a trusted advisor to clients -build long-standing partnerships, deeply understand business problems, formulate the right analytical questions, and deliver insights that create measurable value. Contribute to practice development -participate in business development activities, develop reusable analytical frameworks and methodologies, and help shape the technical direction of Huron's DSML capabilities.# Required Qualifications 5+ years of hands-on experience conducting data science and advanced analytics -not just ad-hoc analysis, but structured analytical projects that drove business decisions. You've framed problems, developed hypotheses, analyzed data, and delivered insights that created measurable impact. Experience leading and developing technical teams -including coaching, mentorship, methodology review, and performance management. Demonstrated ability to build high-performing teams and develop junior talent. Strong Python and SQL programming skills with deep experience in the data science ecosystem (Pandas, NumPy, Scikit-learn, statsmodels, visualization libraries). Comfortable writing production-quality code, not just notebooks. Solid foundation in statistics and machine learning : hypothesis testing, regression analysis, classification, clustering, experimental design, causal inference, and understanding of when different approaches are appropriate for different questions. Experience with deep learning and modern neural architectures -understanding of transformer models, embeddings, transfer learning, and how to leverage foundation models for analytical tasks. You know when ML approaches add value over classical methods, and how to integrate them into rigorous analytical workflows. Proficiency with data platforms : Microsoft Fabric, Snowflake, Databricks, or similar cloud analytics environments. You're comfortable working with large datasets and can optimize queries for performance. Exceptional communication and data storytelling skills -ability to distill complex analyses into clear narratives, create compelling visualizations, lead client meetings, and build trusted relationships with executive audiences. This is non-negotiable. Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, or related quantitative field (or equivalent practical experience). Flexibility to work in a hybrid model with periodic travel to client sites as needed.# Preferred Qualifications Experience in Financial Services, Manufacturing, or Energy & Utilities industries. Background in experimental design, A/B testing, and causal inference methodologies-including propensity score matching, difference-in-differences, or instrumental variables. Hands-on experience with deep learning frameworks (PyTorch, TensorFlow) and neural architectures-including transformers, attention mechanisms, and fine-tuning pretrained models for NLP, time-series, or tabular data applications. Experience building AI-assisted analytical workflows-leveraging foundation model APIs, vector databases, and retrieval systems to accelerate insight extraction from unstructured data. Experience with Bayesian methods, probabilistic programming (PyMC, NumPyro, etc.), or uncertainty quantification in business contexts. Strong visualization and data interface design and development skills using programmatic visualization libraries (Plotly, Altair, D3). Proficiency with AI-assisted rapid data application development using Cursor, Lovable, v0, etc. Experience with time-series analysis, forecasting methods (ARIMA, Prophet, neural forecasting), and demand planning applications. Cloud certifications (Azure Data Scientist, Databricks ML Associate, AWS ML Specialty). Consulting experience or demonstrated ability to work across multiple domains and adapt quickly to new
Apr 30, 2026
Full time
Data Science Manager page is loaded Data Science Managerremote type: Hybridlocations: Belfast - 20 Adelaide Streetposted on: Posted Todayjob requisition id: JR-Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation and navigate constant change. Through a combination of strategy, expertise and creativity, we help clients accelerate operational, digital and cultural transformation, enabling the change they need to own their future. Join our team as the expert you are now and create your future. Data Science Manager We're seeking a Data Science Manager to join the Data Science & Machine Learning team in our Commercial Digital practice, where you'll lead advanced analytics initiatives that transform how Fortune 500 companies make decisions across Financial Services, Manufacturing, Energy & Utilities, and other commercial industries.Managers play a vibrant, integral role at Huron. Their invaluable knowledge reflects in the projects they manage and the teams they lead. Known for building long-standing partnerships with clients, they collaborate with colleagues to solve their most important challenges. Our Managers also spend significant time mentoring junior staff on the engagement team-sharing expertise, feedback, and encouragement. This promotes a culture of respect, unity, collaboration, and personal achievement.This isn't a reporting role or a dashboard factory-you'll own the full analytics lifecycle from hypothesis formulation through insight delivery, while leading and developing a team of data scientists and analysts. You'll work on problems that matter: experimental designs that validate multi-million-dollar strategies, predictive models that surface hidden patterns in complex data, and deep learning pipelines that extract signal from unstructured text, images, and time-series. Our clients are Fortune 500 companies looking for partners who can find the signal in the noise and tell the story that drives action.The variety is real. In your first year, you might lead a customer segmentation and lifetime value analysis for a financial services firm, design and analyze a pricing experiment for a global manufacturer, and build an agentic anomaly detection system for a utility company's operational data-all while developing the next generation of data science talent at Huron. If you thrive on rigorous analysis, clear communication of complex findings, and building high-performing teams, this role is for you.# What You'll Do Lead and mentor junior data scientists and analysts -provide technical guidance, review analytical approaches and code, and support professional development. Foster a culture of intellectual curiosity, rigorous methodology, and clear communication within the team. Manage complex multi-workstream analytics projects -oversee project planning, resource allocation, and delivery timelines. Ensure analyses meet quality standards and client expectations while maintaining methodological rigor. Design and execute end-to-end data science workflows -from problem framing and hypothesis development through exploratory analysis, modeling, validation, and insight delivery. Own the analytical approach and ensure conclusions are defensible. Lead development of both traditional statistical and modern AI-powered analyses -including regression, classification, clustering, causal inference, A/B testing, and modern deep learning approaches using embeddings, transformer architectures, and foundation models for text, time-series, and multimodal analysis. Build predictive and prescriptive models that drive business decisions-customer segmentation, churn prediction, demand forecasting, pricing optimization, risk scoring, and operational efficiency analysis for commercial enterprises. Translate complex analytical findings into actionable insights -create compelling data narratives, develop executive-ready presentations, and communicate technical results to non-technical stakeholders in ways that drive decisions. Serve as a trusted advisor to clients -build long-standing partnerships, deeply understand business problems, formulate the right analytical questions, and deliver insights that create measurable value. Contribute to practice development -participate in business development activities, develop reusable analytical frameworks and methodologies, and help shape the technical direction of Huron's DSML capabilities.# Required Qualifications 5+ years of hands-on experience conducting data science and advanced analytics -not just ad-hoc analysis, but structured analytical projects that drove business decisions. You've framed problems, developed hypotheses, analyzed data, and delivered insights that created measurable impact. Experience leading and developing technical teams -including coaching, mentorship, methodology review, and performance management. Demonstrated ability to build high-performing teams and develop junior talent. Strong Python and SQL programming skills with deep experience in the data science ecosystem (Pandas, NumPy, Scikit-learn, statsmodels, visualization libraries). Comfortable writing production-quality code, not just notebooks. Solid foundation in statistics and machine learning : hypothesis testing, regression analysis, classification, clustering, experimental design, causal inference, and understanding of when different approaches are appropriate for different questions. Experience with deep learning and modern neural architectures -understanding of transformer models, embeddings, transfer learning, and how to leverage foundation models for analytical tasks. You know when ML approaches add value over classical methods, and how to integrate them into rigorous analytical workflows. Proficiency with data platforms : Microsoft Fabric, Snowflake, Databricks, or similar cloud analytics environments. You're comfortable working with large datasets and can optimize queries for performance. Exceptional communication and data storytelling skills -ability to distill complex analyses into clear narratives, create compelling visualizations, lead client meetings, and build trusted relationships with executive audiences. This is non-negotiable. Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, or related quantitative field (or equivalent practical experience). Flexibility to work in a hybrid model with periodic travel to client sites as needed.# Preferred Qualifications Experience in Financial Services, Manufacturing, or Energy & Utilities industries. Background in experimental design, A/B testing, and causal inference methodologies-including propensity score matching, difference-in-differences, or instrumental variables. Hands-on experience with deep learning frameworks (PyTorch, TensorFlow) and neural architectures-including transformers, attention mechanisms, and fine-tuning pretrained models for NLP, time-series, or tabular data applications. Experience building AI-assisted analytical workflows-leveraging foundation model APIs, vector databases, and retrieval systems to accelerate insight extraction from unstructured data. Experience with Bayesian methods, probabilistic programming (PyMC, NumPyro, etc.), or uncertainty quantification in business contexts. Strong visualization and data interface design and development skills using programmatic visualization libraries (Plotly, Altair, D3). Proficiency with AI-assisted rapid data application development using Cursor, Lovable, v0, etc. Experience with time-series analysis, forecasting methods (ARIMA, Prophet, neural forecasting), and demand planning applications. Cloud certifications (Azure Data Scientist, Databricks ML Associate, AWS ML Specialty). Consulting experience or demonstrated ability to work across multiple domains and adapt quickly to new
Martin Veasey Talent Solutions
Northampton, Northamptonshire
Senior Machine Learning Data Scientist - Credit Risk 80,000- 120,000 + Bonus + Benefits (Flexibility to 150k DOE) East Midlands (Hybrid Min. 3 days) The Opportunity There are very few roles in the UK market where you can take ownership of a proven, production-grade credit risk model that is already outperforming competitors - and be given the autonomy to evolve it, refine it and directly influence commercial outcomes. This is one of them. This opportunity sits within a high-growth, data-driven financial services environment where machine learning is not theoretical or exploratory - it is embedded at the core of how the business makes decisions. At the centre of this capability is a highly accurate credit risk model, supported by rich, real-world datasets and a continuous feedback loop of internal and external lending outcomes. The model is already delivering strong predictive performance, but the real value lies in how it is developed from here. This opportunity represents a natural evolution of an already successful machine learning capability, offering the chance to take ownership of a proven model and shape its future direction. The Role This is a senior, hands-on data science role focused on credit risk modelling within a commercial lending environment. You will take ownership of the core modelling framework, working directly on probability of default models and broader decisioning logic that underpins lending strategy. The emphasis is on refinement, optimisation and continuous improvement rather than building from scratch. You will be responsible for the intellectual core of the models: Feature engineering across financial, behavioural and transactional data Algorithm selection and tuning (logistic regression, gradient boosting, ensemble methods) Model validation, performance optimisation and ongoing recalibration Ensuring models remain robust in changing economic conditions You will not be responsible for infrastructure, pipelines or deployment. A dedicated engineering team manages AWS and production environments, allowing you to focus on modelling and analytics. This is a highly visible role with direct exposure to senior stakeholders. You will be expected to explain model performance, justify modelling decisions and translate technical outputs into clear commercial insight. The Environment This is a business that understands the value of data but is still at a stage where impact is direct and visible. There is: No large data science hierarchy No separation between thinking and execution No dilution of responsibility across multiple teams You will operate as the central subject matter expert within a collaborative technical environment, with the autonomy to influence both modelling direction and commercial outcomes. Over time, there is a clear pathway to build out a team and evolve into a leadership role. However, the immediate focus is on hands-on ownership and delivery. What This Role Is Not This role will not suit individuals who: Have moved fully into leadership and no longer build models themselves Prefer purely strategic or advisory positions without technical ownership Are focused on infrastructure, MLOps or engineering rather than modelling Want a large team or established function around them from day one This is a role for someone who wants to remain close to the detail and take responsibility for outcomes. The Ideal Profile You are a hands-on machine learning data scientist with deep experience in credit risk modelling. You are currently building, refining and optimising models yourself, not delegating that work. You are likely to have developed your career within: SME lending, fintech or banking environments Credit risk, underwriting or decision science functions You will have: Strong experience building probability of default or credit scoring models Advanced Python capability Experience with algorithms such as logistic regression, XGBoost, LightGBM or similar A strong understanding of model evaluation (ROC-AUC, Gini, precision/recall) Experience working with complex financial or behavioural datasets You understand how your work impacts: Approval rates Default risk Commercial performance You are comfortable discussing modelling decisions in depth with technical stakeholders, but equally able to simplify complex concepts for non-technical audiences. Qualifications You will typically have a strong academic foundation in a quantitative discipline such as Mathematics, Statistics, Data Science, Engineering, Physics or a closely related field. Many candidates at this level will hold a Master's degree or equivalent advanced qualification, although this is not essential where there is clear evidence of deep practical expertise in credit risk modelling and machine learning. What is critical is a strong grounding in mathematical thinking, statistical modelling and problem solving, combined with the ability to apply that knowledge in a commercial environment. Why This Role Stands Out Ownership of a high-performing, production-grade credit risk model Access to rich, real-world data with continuous feedback loops Direct influence on lending decisions and commercial performance Strong engineering support, allowing full focus on modelling High visibility with senior leadership Clear pathway to future Head of AI / Machine Learning role Opportunity to shape the next phase of a proven data capability Package & Flexibility 80,000- 120,000 base salary Bonus up to 15% Flexibility to 150,000 for exceptional candidates Hybrid working (East Midlands, typically 2-3 days onsite with flexibility)
Apr 29, 2026
Full time
Senior Machine Learning Data Scientist - Credit Risk 80,000- 120,000 + Bonus + Benefits (Flexibility to 150k DOE) East Midlands (Hybrid Min. 3 days) The Opportunity There are very few roles in the UK market where you can take ownership of a proven, production-grade credit risk model that is already outperforming competitors - and be given the autonomy to evolve it, refine it and directly influence commercial outcomes. This is one of them. This opportunity sits within a high-growth, data-driven financial services environment where machine learning is not theoretical or exploratory - it is embedded at the core of how the business makes decisions. At the centre of this capability is a highly accurate credit risk model, supported by rich, real-world datasets and a continuous feedback loop of internal and external lending outcomes. The model is already delivering strong predictive performance, but the real value lies in how it is developed from here. This opportunity represents a natural evolution of an already successful machine learning capability, offering the chance to take ownership of a proven model and shape its future direction. The Role This is a senior, hands-on data science role focused on credit risk modelling within a commercial lending environment. You will take ownership of the core modelling framework, working directly on probability of default models and broader decisioning logic that underpins lending strategy. The emphasis is on refinement, optimisation and continuous improvement rather than building from scratch. You will be responsible for the intellectual core of the models: Feature engineering across financial, behavioural and transactional data Algorithm selection and tuning (logistic regression, gradient boosting, ensemble methods) Model validation, performance optimisation and ongoing recalibration Ensuring models remain robust in changing economic conditions You will not be responsible for infrastructure, pipelines or deployment. A dedicated engineering team manages AWS and production environments, allowing you to focus on modelling and analytics. This is a highly visible role with direct exposure to senior stakeholders. You will be expected to explain model performance, justify modelling decisions and translate technical outputs into clear commercial insight. The Environment This is a business that understands the value of data but is still at a stage where impact is direct and visible. There is: No large data science hierarchy No separation between thinking and execution No dilution of responsibility across multiple teams You will operate as the central subject matter expert within a collaborative technical environment, with the autonomy to influence both modelling direction and commercial outcomes. Over time, there is a clear pathway to build out a team and evolve into a leadership role. However, the immediate focus is on hands-on ownership and delivery. What This Role Is Not This role will not suit individuals who: Have moved fully into leadership and no longer build models themselves Prefer purely strategic or advisory positions without technical ownership Are focused on infrastructure, MLOps or engineering rather than modelling Want a large team or established function around them from day one This is a role for someone who wants to remain close to the detail and take responsibility for outcomes. The Ideal Profile You are a hands-on machine learning data scientist with deep experience in credit risk modelling. You are currently building, refining and optimising models yourself, not delegating that work. You are likely to have developed your career within: SME lending, fintech or banking environments Credit risk, underwriting or decision science functions You will have: Strong experience building probability of default or credit scoring models Advanced Python capability Experience with algorithms such as logistic regression, XGBoost, LightGBM or similar A strong understanding of model evaluation (ROC-AUC, Gini, precision/recall) Experience working with complex financial or behavioural datasets You understand how your work impacts: Approval rates Default risk Commercial performance You are comfortable discussing modelling decisions in depth with technical stakeholders, but equally able to simplify complex concepts for non-technical audiences. Qualifications You will typically have a strong academic foundation in a quantitative discipline such as Mathematics, Statistics, Data Science, Engineering, Physics or a closely related field. Many candidates at this level will hold a Master's degree or equivalent advanced qualification, although this is not essential where there is clear evidence of deep practical expertise in credit risk modelling and machine learning. What is critical is a strong grounding in mathematical thinking, statistical modelling and problem solving, combined with the ability to apply that knowledge in a commercial environment. Why This Role Stands Out Ownership of a high-performing, production-grade credit risk model Access to rich, real-world data with continuous feedback loops Direct influence on lending decisions and commercial performance Strong engineering support, allowing full focus on modelling High visibility with senior leadership Clear pathway to future Head of AI / Machine Learning role Opportunity to shape the next phase of a proven data capability Package & Flexibility 80,000- 120,000 base salary Bonus up to 15% Flexibility to 150,000 for exceptional candidates Hybrid working (East Midlands, typically 2-3 days onsite with flexibility)
